WO2019226765A1 - Procédés et systèmes de traitement automatisé de données - Google Patents

Procédés et systèmes de traitement automatisé de données Download PDF

Info

Publication number
WO2019226765A1
WO2019226765A1 PCT/US2019/033510 US2019033510W WO2019226765A1 WO 2019226765 A1 WO2019226765 A1 WO 2019226765A1 US 2019033510 W US2019033510 W US 2019033510W WO 2019226765 A1 WO2019226765 A1 WO 2019226765A1
Authority
WO
WIPO (PCT)
Prior art keywords
seconds
condition
computer system
utilization
computer
Prior art date
Application number
PCT/US2019/033510
Other languages
English (en)
Inventor
Allen Weldon SMITH
Aaron Webster SMITH
Original Assignee
Sidereal Technologies, Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sidereal Technologies, Llc filed Critical Sidereal Technologies, Llc
Publication of WO2019226765A1 publication Critical patent/WO2019226765A1/fr

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
    • H04L9/3239—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3297—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials involving time stamps, e.g. generation of time stamps
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees

Definitions

  • a computer-implemented method for automatically processing data between a central repository, general ledger, distributed repository, distributed ledger,“proof of work” reward systems and/or hash algorithms with a computer system may comprise: (a) detecting a plurality of characteristics of the computer system, over a computer network, to identify a plurality of actual conditions correlating to the plurality of characteristics, wherein the plurality of characteristics comprise at least a graphics processing unit (“GPU”) utilization of the computer system and a central processing unit (“CPU”) utilization of the computer system; (b) comparing, through one or more computer processors, the plurality of actual conditions with a plurality of reference conditions; (c) determining, through the one or more computer processors, whether the computer system is idle based on the plurality of actual conditions and the plurality of reference conditions; and (d) mining one or more cryptocurrencies with the computer system upon determining the computer system is idle in (c).
  • GPU graphics processing unit
  • CPU central processing unit
  • a method disclosed herein can comprise: detecting a plurality of characteristics of said computer system, over a computer network, to identify a plurality of actual conditions correlating to said plurality of characteristics, wherein said plurality of characteristics comprise at least a graphics processing unit (“GPU”) utilization of said computer system or a central processing unit (“CPU”) utilization of said computer system.
  • a method disclosed herein can comprise comparing, through one or more computer processors, a plurality of actual conditions with a plurality of reference conditions.
  • a method disclosed herein can comprise determining, through one or more computer processors, whether a computer system is idle based on a plurality of actual conditions and said plurality of reference conditions.
  • a method disclosed herein can comprise mining one or more cryptocurrencies with a computer system upon determining that the computer system is idle.
  • a method disclosed herein can comprise mining one or more cryptocurrencies with a computer system upon determining that the computer system is idle.
  • determining whether the computer system is idle may comprise comparing the plurality of actual conditions with the plurality of reference conditions.
  • the plurality of reference conditions may correlate to the plurality of
  • the plurality of characteristics may comprise the GPU utilization of the computer system and the CPU utilization of the computer system.
  • the plurality of reference conditions may comprise a condition that the GPU utilization is less than about 10%. In some embodiments, the plurality of reference conditions may comprise a condition that the CPU utilization is less than about 20%.
  • the plurality of characteristics may further comprise a mouse movement of the computer system.
  • the plurality of reference conditions may comprise a condition that the mouse movement is less than about 5 pixels for at least about 3 minutes.
  • the plurality of characteristics may further comprise a keyboard input of the computer system.
  • the plurality of reference conditions may comprise a condition that the keyboard input is not detected for at least about 3 minutes.
  • the plurality of characteristics may further comprise a network utilization of the computer system.
  • the plurality of reference conditions may comprise a condition that the network utilization is less than about 5%.
  • the plurality of characteristics further may comprise an inactive period of the computer system.
  • the plurality of reference conditions may comprise a condition that the inactive period is between 18:00 (Pacific Standard Time) and 6:00 (Pacific Standard Time).
  • the plurality of characteristics may further comprise a runtime of the computer system.
  • the plurality of reference conditions may comprise a previous runtime of the computer system. In some embodiments, the plurality of characteristics may further comprise an up-time of the computer system. In some embodiments, the plurality of reference conditions may comprise a condition that the up-time is at least about 14 hours per day. In some embodiments, the plurality of characteristics further may comprise a mouse movement, a keyboard input, and a network utilization of the computer system.
  • the plurality of characteristics may further comprise a mouse movement, a keyboard input, a network utilization, an inactive period, a runtime, and an up-time of the computer system.
  • the hash algorithms may comprise SHA-256d, Scrypt, SHA-256, CryptoNote, NeoScrypt, 1CC/2CC/TWN, ECDSA, XI 1, RIPEMD160, CryptoNight, SHA3-512, Omnicore , PoS, xl7, Stellar Consensus Protocol (SCP) , Lyra2RE, Ethash, SHA-3, DPoS, Equihash, onixCoin, Genomics, pharmaceutical simulations, financial batch processing, and lab sample analysis.
  • FIG. 1 shows an example of a flowchart of a computer-implemented method for automatically processing data between a central repository, general ledger, distributed repository, distributed ledger,“proof of work” reward systems and/or hash algorithms with a computer system;
  • FIG. 2 shows an example of a decision loop process of the computer-implemented method disclosed herein
  • FIG. 3 shows an example of a block diagram of the system executing the computer- implemented method disclosed herein;
  • FIG. 4 shows an example of a client site computer system
  • FIG. 5 shows an example of a dashboard that is executed on a central operation control center (“COCC”);
  • COCC central operation control center
  • FIG. 6 shows an example of a summary of a single miner showed on the screen of the COCC.
  • FIG. 7 shows a computer control system that is programmed or otherwise configured to implement methods provided herein.
  • any percentage range, ratio range, or integer range is to be understood to include the value of any integer within the recited range and, when appropriate, fractions thereof (such as one tenth and one hundredth of an integer), unless otherwise indicated.
  • the terms“a” and“an” as used herein refer to“one or more” of the enumerated components unless otherwise indicated or dictated by its context.
  • the use of the alternative e.g.,“or” should be understood to mean either one, both, or any combination thereof of the alternatives.
  • the terms“include” and“comprise” are used synonymously.
  • the term“about” or“approximately” can mean within an acceptable error range for the particular value as determined by one of ordinary skill in the art, which will depend in part on how the value is measured or determined, e.g., the limitations of the measurement system.
  • “about” can mean plus or minus 10%, per the practice in the art.
  • “about” can mean a range of plus or minus 20%, plus or minus 10%, plus or minus 5%, or plus or minus 1% of a given value.
  • the term can mean within an order of magnitude, within 5-fold, or within 2-fold, of a value.
  • the central repository may be an electronic storage unit.
  • the electronic storage unit may be a data storage unit for storing data.
  • the distributed repository may be an electronic storage unit.
  • the electronic storage unit may be a data storage unit for storing data.
  • the general ledger may comprise all the accounts for recording transactions.
  • the transactions may be financial transactions.
  • the financial transaction may include, but not limited to, an individual or company’s assets, liabilities, owners’ equity, revenue, and expenses.
  • the transactions may be related to anything having a financial value.
  • the general ledger may be an enterprise resource planning (ERP) system.
  • ERP enterprise resource planning
  • the general ledger may work as a central repository for storing accounting data.
  • the accounting data may include cash management, fixed assets, purchasing and projects.
  • the general ledger may hold financial and non-fmancial data for an individual or organization.
  • the distributed ledger may be a type of database that is shared, replicated, and/or synchronized among the participants of a decentralized network.
  • the distributed ledger may record the transactions, such as the exchange of assets or data, among the participants in the decentralized network. Participants in the network may govern and agree by consensus on the updates to the records in the ledger.
  • No central authority or third-party mediator, such as a financial institution or clearinghouse, may be involved. Every record in the distributed ledger may have a timestamp and unique cryptographic signature, thus making the ledger an auditable, immutable history of all transactions in the network.
  • the distributed ledger may be a database held and updated independently by each node in a large network.
  • a distribution associated with the distributed ledger may be records not communicated to various nodes by a central authority. The records may be independently constructed and held by each node. In this situation, every single node on the network may process every transaction, coming to its own conclusions and then voting on those conclusions to make certain the majority agree with the conclusions. Once there is this consensus, the distributed ledger may be updated, and all nodes may maintain their own identical copy of the ledger.
  • the distributed ledger may permanently record, in a sequential chain of cryptographic hash-linked blocks, the history of asset exchanges that may take place between the participants in the network. All the confirmed and validated transaction blocks may be linked and chained from the beginning of the chain to the most current block.
  • the linked blocks may be blockchain.
  • the blockchain may act as a single source of truth, and members in a blockchain network may view only those transactions that are relevant to them.
  • member nodes in a blockchain network may use a consensus protocol to agree on ledger content, and cryptographic hashes and digital signatures to ensure the integrity of transactions.
  • Consensus may ensure that the shared ledgers are exact copies. Consensus may lower the risk of fraudulent transactions, because tampering would have to occur across many places at exactly the same time.
  • Cryptographic hashes such as the SHA256 computational algorithm, may ensure that any alteration to transaction input results in a different hash value being computed, which indicates potentially compromised transaction input.
  • Digital signatures may ensure that transactions originated from senders and not imposters.
  • the decentralized blockchain network may prevent any single participant or group of participants from controlling the underlying infrastructure or undermining the entire system. Participants in the network may be all equal, adhering to the same protocols. Participants may be individuals, state actors, organizations, or a combination of all these types of participants.
  • the system may record the chronological order of transactions with all nodes agreeing to the validity of transactions using the chosen consensus model. The result may be transactions that cannot be altered or reversed, unless the change is agreed to by all participants in the network in a subsequent transaction.
  • the computer-implemented method for automatically processing data disclosed herein may comprise detecting a plurality of characteristics of the computer system, over a computer network, to identify a plurality of actual conditions correlating to the plurality of characteristics.
  • the plurality of characteristics may comprise at least information about one or more processors such as a graphics processing unit (“GPU”) utilization of the computer system and a central processing unit (“CPU”) utilization of the computer system.
  • the plurality of characteristics may further comprise information about I/O devices such as a mouse movement, a keyboard input, a network utilization, an inactive period, a runtime, and an up-time of the computer system.
  • the plurality of characteristics may also comprise, but not limited to, memory consumption, fan usage, power consumption, a temperature, a sound and various others.
  • the computer-implemented method for automatically processing data may comprise detecting a GPU utilization of the computer system.
  • the GPU utilization may represent the usage of the GPU of the computer system.
  • the GPU may be, but not limited to, a dedicated graphics card, integrated graphics, hybrid graphics processing, stream processing and general purpose GPU, or external GPU.
  • the GPU may be, but not limited to, GeForce GTX, nVidia Titan X, Radeon HD, Radeon r5, r7, r9 and RX series, nVidia Grid, Radeon Sky, nVidia Quadro, nVidia Titan X, AMD FirePro, Radeon Pro, Cloud Workstation, nVidia Tesla, AMD FireStream, nVidia Tesla, Radeon Instinct, Automated/Driverless car, or nVidia Drive PX.
  • the GPU may comprise one or more caches configured to interact with other components of the computer system.
  • the GPU may comprise at least one GPU processor.
  • the GPU processor may perform operations in a graphics pipeline to render objects into a frame. For example, the operations may include transformation and lighting, triangle assembly, rasterization, shading, texturizing, etc.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the GPU utilization with a reference condition of the GPU utilization.
  • the actual condition of the GPU utilization may be a real-time GPU utilization.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 1%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 5%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 10%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 15%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 20%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 25%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 30%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 35%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 40%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 45%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 50%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 55%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 60%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 65%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 70%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 75%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 80%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 85%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 90%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is less than about 95%.
  • the reference condition of the GPU utilization may comprise a condition that the GPU utilization is at most about 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, 5% or less.
  • the process of comparing an actual condition of GPU utilization with a reference condition of GPU utilization may be performed about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds, 20 seconds, 21 seconds, 22 seconds, 23 seconds, 24 seconds, 25 seconds, 26 seconds, 27 seconds, 28 seconds, 29 seconds, 30 seconds, 31 seconds, 32 seconds, 33 seconds, 34 seconds, 35 seconds, 36 seconds, 37 seconds, 38 seconds, 39 seconds, 40 seconds, 41 seconds, 42 seconds, 43 seconds, 44 seconds, 45 seconds, 46 seconds, 47 seconds, 48 seconds, 49 seconds, 51 second, 52 seconds, 53 seconds, 54 seconds, 55 seconds, 56 seconds, 57 seconds, 58 seconds, 59 seconds, 1 minute, 2 minutes, 3 minutes, or 4 minutes.
  • the process of comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization may be performed at least about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds,
  • the GPU usage or utilization can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications.
  • the usage of each processing unit may be individually monitored.
  • the usage of the overall GPU may be monitored.
  • the computer-implemented method for automatically processing data may comprise detecting a CPU utilization of the computer system.
  • the CPU utilization may represent the usage of the CPU of the computer system.
  • the CPU may comprise at least one CPU processor.
  • the CPU processor may execute programs of the computer system.
  • the programs of the computer system may an operating system.
  • the operating system may be, but not limited to, Arthur, ARX, MOS, RISC iX, RISC OS, AmigaOS, Amiga Unix, Apple DOS, Apple Pascal, ProDOS, GS/OS, GNO/ME, Apple SOS, Apple Lisa, Apple Macintosh, Classic Mac OS, A/UX (UNIX System V with BSD extensions), Copland, MkLinux, Pink, Rhapsody, NeXTSTEP, macOS (formerly Mac OS X and OS X), macOS Server (formerly Mac OS X Server and OS X Server), IBM AIX (Apple-customized), Newton OS, iOS (formerly iPhone OS), Apple watchOS, Apple tvOS, A/ROSE, Domain/OS, Atari DOS, Atari TOS, Atari MultiTOS, XTS- 400, BeOS, Bel A, BeOS r5.ld0, Unix, MINI-UNIX, PWB/UNIX, USG, CB Unix, BESYS, Plan 9 from Bell Labs. In
  • the programs executed by the CPU may control other components of the computer system.
  • Software may be application programs.
  • the application programs may be controlled by application processors.
  • the CPU may further comprise other hardware.
  • the CPU utilization may track CPU performance regressions or improvements.
  • the CPU utilization may be reported in a plurality of operating systems. For instance, in Window’s system, the CPU utilization may be reported in Task Manager (taskmgr.exe), Resource Monitor (resmon.exe), and Performance Monitor (perfmon.exe).
  • Task Manager taskmgr.exe
  • Resource Monitor resource Monitor
  • perfmon.exe Performance Monitor
  • the CPU utilization may vary according to different computing activities.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the CPU utilization with a reference condition of CPU utilization.
  • the reference condition of CPU utilization may comprise a condition wherein CPU utilization is less than about 1%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 5%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 10%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 15%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 20%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 25%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 30%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 35%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 40%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 45%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 50%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 55%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 60%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 65%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 70%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 75%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 80%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 85%.
  • the reference condition of the CPU utilization may comprise a condition that the CPU utilization is less than about 90%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is less than about 95%.
  • the reference condition of the CPU utilization may comprise a condition wherein CPU utilization is at most about 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, 5% or less.
  • the process of comparing an actual condition of the CPU utilization with a reference condition of CPU utilization may be performed about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds, 20 seconds, 21 seconds, 22 seconds, 23 seconds, 24 seconds, 25 seconds, 26 seconds, 27 seconds, 28 seconds, 29 seconds, 30 seconds, 31 seconds, 32 seconds, 33 seconds, 34 seconds, 35 seconds, 36 seconds, 37 seconds, 38 seconds, 39 seconds, 40 seconds, 41 seconds, 42 seconds, 43 seconds, 44 seconds, 45 seconds, 46 seconds, 47 seconds, 48 seconds, 49 seconds, 51 second, 52 seconds, 53 seconds, 54 seconds, 55 seconds, 56 seconds, 57 seconds, 58 seconds, 59 seconds, 1 minute, 2 minutes, 3 minutes, or 4 minutes.
  • the process of comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization may be performed at least about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds,
  • the CPU usage or utilization can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications.
  • the usage of each processing unit may be individually monitored.
  • the usage of the overall CPU may be monitored.
  • the computer-implemented method for automatically processing data may comprise detecting a network utilization of the computer system.
  • the network utilization may represent the usage of the network of the computer system.
  • the network utilization may represent the usage of a network connecting one or more computer systems.
  • the network utilization may represent the usage of multiple networks, each of which connecting to one or more computer systems.
  • the multiple networks may present at a geographic location.
  • the multiple networks may present at different geographic locations.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the network utilization with a reference condition of the network utilization.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 1%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 5%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 10%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 15%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 20%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 25%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 30%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 35%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 40%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 45%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 50%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 55%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 60%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 65%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 70%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 75%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 80%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 85%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 90%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is less than about 95%.
  • the reference condition of the network utilization may comprise a condition wherein the network utilization is at most about 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, 5% or less.
  • the process of comparing an actual condition of the network utilization with a reference condition of the network utilization may be performed about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds,
  • the process of comparing an actual condition of the network utilization with a reference condition of the network utilization may be performed at least about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds, 20 seconds, 21 seconds, 22 seconds, 23 seconds, 24 seconds, 25 seconds, 26 seconds, 27 seconds, 28 seconds, 29 seconds, 30 seconds, 31 seconds, 32 seconds, 33 seconds, 34 seconds, 35 seconds, 36 seconds, 37 seconds, 38 seconds, 39 seconds, 40 seconds, 41 seconds, 42 seconds, 43 seconds, 44 seconds, 45 seconds, 46 seconds, 47 seconds, 48 seconds, 49 seconds, 51 second,
  • the process of comparing an actual condition of the network utilization with a reference condition of the network utilization may be performed less than about every 1 second.
  • the network usage or utilization can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications.
  • the computer-implemented method for automatically processing data may comprise detecting a mouse movement of the computer system.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the mouse movement with a reference condition of the mouse movement.
  • the reference condition of the mouse movement may comprise a condition that the mouse movement is less than about 1 pixel for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition that the mouse movement is less than about 2 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition that the mouse movement is less than about 3 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 4 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 5 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 6 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 7 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 8 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 9 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is less than about 10 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the mouse movement may comprise a condition wherein the mouse movement is equal to or greater than 10 pixels for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute,
  • the process of comparing an actual condition of the mouse movement with a reference condition of the mouse movement may be performed about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds,
  • the process of comparing an actual condition of the mouse movement with a reference condition of the mouse movement may be performed at least about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds, 20 seconds, 21 seconds, 22 seconds, 23 seconds, 24 seconds, 25 seconds, 26 seconds, 27 seconds, 28 seconds, 29 seconds, 30 seconds, 31 seconds, 32 seconds, 33 seconds, 34 seconds, 35 seconds, 36 seconds,
  • the process of comparing an actual condition of the mouse movement with a reference condition of the mouse movement may be performed less than about every 1 second.
  • the mouse movement can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications.
  • the computer-implemented method for automatically processing data may comprise detecting a keyboard input of the computer system.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the keyboard input with a reference condition of the mouse movement.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for at least about 1 second, 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 6 minutes, or greater.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 1 second.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 30 seconds.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 1 minute.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 2 minutes.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 3 minutes.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 1 second.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 4 minutes.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 5 minutes.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 6 minutes.
  • the reference condition of the keyboard input may comprise a condition wherein the keyboard input is not detected for about 7 minutes.
  • the process of comparing an actual condition of the keyboard input with a reference condition of the keyboard input may be performed about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds, 7 seconds, 8 seconds, 9 seconds, 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, 16 seconds, 17 seconds, 18 seconds, 19 seconds,
  • the process of comparing an actual condition of the keyboard input with a reference condition of the keyboard input may be performed at least about every 1 second, 2 seconds, 3 seconds, 4 seconds, 5 seconds, 6 seconds,
  • the process of comparing an actual condition of the keyboard input with a reference condition of the keyboard input may be performed less than about every 1 second.
  • the keyboard input can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications.
  • the computer-implemented method for automatically processing data may comprise detecting an inactive period of the computer system.
  • the inactive period of the computer system may be a specific time range.
  • the specific time range may be the time range between/or after a subject leave their place of work and/or before a subject start to work again the next day.
  • the inactive period may be between 18:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time).
  • the inactive period may be between 17:00 (Pacific Standard Time) and 6:00 (Pacific Standard Time).
  • the inactive period may be between 18:00 (Pacific Standard Time) and 7:00 ( Pacific Standard Time).
  • the inactive period may be between 19:00 ( Pacific Standard Time) and 7:00 (Pacific Standard Time).
  • the inactive period may be between 20:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time).
  • the inactive period may be between 21 :00 (Pacific Standard Time) and 6:00 ( Pacific Standard Time).
  • the inactive period may be between 21 :00 (Pacific Standard Time) and 7:00 ( Pacific Standard Time).
  • the inactive period may be between 22:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time).
  • the inactive period may be between 22:00 ( Pacific Standard Time) and 7:00 (Pacific Standard Time).
  • the inactive period may be between 23:00 (Pacific Standard Time) and 6:00 ( Pacific Standard Time).
  • the inactive period may be between 23:00 (Pacific Standard Time) and 7:00 ( Pacific Standard Time).
  • the inactive period of the computer system may be any time range defined by the computer-implemented method.
  • the inactive period can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications
  • the inactive period of the computer system may be predetermined to remain the same for a period of time.
  • the period of time may be at least about a day, two days, three days, four days, five days, six days, a week, two weeks, three weeks, a month, two months, three months, four months, five months, six months, seven months, eight months, nine months, ten months, eleven months, one year, or longer.
  • the inactive period of the computer system may be predetermined to remain between 18:00 (Pacific Standard Time) and 6:00 (Pacific Standard Time) for one month.
  • the inactive period of the computer system may change periodically.
  • the frequency of the change of the inactive period may be at least every day, two days, three days, four days, five days, six days, a week, two weeks, three weeks, a month, two months, three months, four months, five months, six months, seven months, eight months, nine months, ten months, eleven months, one year, or longer.
  • the inactive period of the computer system may be predetermined to be between 18:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time) for one month, but may change to between 20:00 (Pacific Standard Time) and 6:00 (Pacific Standard Time) for the following month.
  • the frequency of change may be determined by one or more algorithms.
  • the one or more algorithms may include machine learning algorithms.
  • the machine learning algorithms may comprise supervised learning algorithms, unsupervised learning algorithms, semi- supervised learning algorithms, reinforcement learning algorithms, deep learning algorithms, or any combination thereof.
  • the machine learning algorithms may also comprise Support Vector Machine (SVM), Naive Bayes (NB), Quadratic Discriminant Analysis (QDA), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), or Multilayer Perceptron (MLP).
  • SVM Support Vector Machine
  • NB Naive Bayes
  • QDA Quadratic Discriminant Analysis
  • KNN K-Nearest Neighbors
  • LDA Linear Discriminant Analysis
  • MLP Multilayer Perceptron
  • the computer-implemented method for automatically processing data may comprise detecting a runtime of the computer system.
  • the runtime of the computer system may comprise information regarding the actual conditions of the characteristics of the computer system during a current run.
  • the actual conditions of the characteristics of the computer system may be the actual condition of the GUP utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period, or any combination thereof.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the runtime with a reference condition of the runtime.
  • the reference condition of the runtime may comprise a previous runtime of the computer system.
  • the reference condition of the runtime may comprise two previous runtimes of the computer system.
  • the reference condition of the runtime may comprise three previous runtimes of the computer system.
  • the reference condition of the runtime may comprise four previous runtimes of the computer system.
  • the reference condition of the runtime may comprise five previous runtimes of the computer system.
  • the reference condition of the runtime may comprise six previous runtimes of the computer system.
  • the reference condition of the runtime may comprise seven previous runtimes of the computer system.
  • the reference condition of the runtime may comprise at least one, two, three, four, five, six, seven or more previous runtimes of the computer system.
  • the previous runtime of the computer system may comprise information regarding previous actual conditions of the characteristics of the computer system during a previous run.
  • the previous actual conditions of the characteristics of the computer system may be the previous actual condition of the GUP utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period, or any combination thereof.
  • the process of comparing, through one or more computer processors, an actual condition of the runtime with a reference condition of the runtime may serve as a decisive factor for determining whether the computer system is idle when other actual conditions do not meet their respective reference conditions.
  • the runtime can be monitored or tracked by an embedded system function, program, backed-in tools (e.g., Task manager) or any external applications.
  • the previous runtimes and/or any runtime may be stored in a database.
  • a database can be stored in computer readable format.
  • a computer processor may be configured to access the data stored in the computer readable memory.
  • a computer system may be used to analyze the data to obtain a result.
  • the result may be stored remotely or internally on storage medium, and communicated to personnel such as medication professionals.
  • the result may be, but not limited to, whether the actual condition of the runtime may meet with at least one, two, three, four, five, six, seven or more previous runtimes of the computer system.
  • the computer system may be operatively coupled with components for transmitting the result.
  • Components for transmitting can include wired and wireless components.
  • wired communication components can include a Universal Serial Bus (USB) connection, a coaxial cable connection, an Ethernet cable such as a Cat5 or Cat6 cable, a fiber optic cable, or a telephone line.
  • wireless communication components can include a Wi-Fi receiver, a component for accessing a mobile data standard such as a 3G or 4G LTE data signal, or a Bluetooth receiver.
  • all data in the storage medium may be collected and archived to build a data warehouse.
  • the data warehouse may be used by individuals or enterprises to analyze the utilization of the computer system.
  • the data warehouse may be integrated with other platforms.
  • the other platforms may be any platforms, for instance, but not limited to, medical research platform, scientific research platform, artificial intelligence platform, data collection platform, and/or data analytic platform.
  • the computer system can transmit data to a database or server.
  • a database or server can be a cloud server.
  • the computer system can transmit data wirelessly via a Wi-Fi, or Bluetooth connection.
  • the computer system may comprise centralized data processing.
  • the centralized data processing may be cloud-based, internet-based, locally accessible network (LAN)-based, or a dedicated reading center using pre-existent or new platforms. Up-time
  • the computer-implemented method for automatically processing data may comprise detecting an up-time of the computer system.
  • the up-time may represent the time during which the computer system may be active.
  • the computer-implemented method for automatically processing data may comprise comparing, through one or more computer processors, an actual condition of the up-time with a reference condition of the up-time.
  • the reference condition of the up-time may be an expected up-time of the computer system.
  • the expected up-time may be the time that the computer system is expected to be active.
  • the expected up-time may be obtained by any statistical or mathematical techniques.
  • the expected up-time may also be obtained by one or more algorithms.
  • the one or more algorithms may include machine learning algorithms.
  • the machine learning algorithms may comprise supervised learning algorithms, unsupervised learning algorithms, semi-supervised learning algorithms, reinforcement learning algorithms, deep learning algorithms, or any combination thereof.
  • the machine learning algorithms may also comprise Support Vector Machine (SVM), Naive Bayes (NB), Quadratic Discriminant Analysis (QDA), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), and Multilayer Perceptron (MLP).
  • SVM Support Vector Machine
  • NB Naive Bayes
  • QDA Quadratic Discriminant Analysis
  • KNN K-Nearest Neighbors
  • LDA Linear Discriminant Analysis
  • MLP Multilayer Perceptron
  • the expected up-time may be about 1 hour per day.
  • the expected up-time may be about 2 hours per day.
  • the expected up-time may be about 3 hours per day.
  • the expected up-time may be about 4 hours per day.
  • the expected up-time may be about 5 hours per day.
  • the expected up time may be about 6 hours per day.
  • the expected up-time may be about 7 hours per day.
  • the expected up-time may be about 8 hours per day.
  • the expected up-time may be about 9 hours per day.
  • the expected up-time may be about 10 hours per day.
  • the expected up-time may be about 11 hours per day.
  • the expected up-time may be about 12 hours per day.
  • the expected up-time may be about 13 hours per day.
  • the expected up-time may be about 14 hours per day.
  • the expected up-time may be about 15 hours per day.
  • the expected up-time may be about 16 hours per day.
  • the expected up-time may be about 17 hours per day.
  • the expected up-time may be about 18 hours per day.
  • the expected up-time may be about 19 hours per day.
  • the expected up- time may be about 20 hours per day.
  • the expected up-time may be about 21 hours per day.
  • the expected up-time may be about 22 hours per day.
  • the expected up-time may be about 23 hours per day.
  • the expected up-time may be at most about 24 hours per day, 23 hours per day, 22 hours per day, 21 hours per day, 20 hours per day, 19 hours per day, 18 hours per day, 17 hours per day, 16 hours per day, 15 hours per day, 14 hours per day, 13 hours per day, 12 hours per day, 11 hours per day, 10 hours per day, 9 hours per day, or less.
  • the actual condition of the up-time may be a current up-time.
  • the actual condition of the up-time may be a historic up-time.
  • the historic up-time may be a previous up-time of the computer system.
  • the historic up-time may be an average of two previous up-times of the computer system.
  • the historic up-time may be an average of three previous up-times of the computer system.
  • the historic up-time may be an average of four previous up-times of the computer system.
  • the historic up-time may be an average of five previous up-times of the computer system.
  • the historic up-time may be an average of six previous up-times of the computer system.
  • the historic up-time may be an average of seven previous up-times of the computer system.
  • the historic up-time may be an average of at least two, three, four, five, six, seven or more previous up-time of the computer system.
  • any other characteristics of the computer system for instance, but not limited to, memory consumption, fan usage, power consumption, a temperature, a sound and various others— ay be used by the computer-implemented method alone or in
  • the computer-implemented method for automatically processing data may comprise determining, through one or more computer processors, whether the computer system is idle based on the plurality of actual conditions and the plurality of reference conditions.
  • the process of determining whether the computer system is idle may comprise comparing the plurality of actual conditions with the plurality of reference conditions.
  • a computer system may be determined to be idle based on at least one of the characteristics described herein.
  • the one or more characteristics for determining the idleness may vary with respect to time.
  • the one or more characteristics for determining the idleness may or may not be the same for different computer systems.
  • the reference condition associated with each characteristic may be predetermined.
  • the reference condition may comprise a threshold which is determined based on empirical data or historical data collected during a period of time. Such empirical data or historical data may be collected from computer systems of the similar set up. Alternatively, such empirical data or historical data may be collected from computer systems regardless of the type or set up.
  • the reference condition associated with each characteristic may be varied or updated along with time.
  • the reference condition associated with each characteristic may be predetermined by an administer of the system.
  • the reference condition associated with each characteristic may be determined using machine learning algorithms. The reference conditions may be automatically determined and updated without human intervention.
  • the process of determining whether the computer system is idle may be based on one or more characteristic of the computer system.
  • the one characteristic of the computer system may be GPU utilization.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization. For instance, the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition wherein the GPU utilization is less than about 10%.
  • any one characteristic of the computer system for instance, network utilization, may be used to determine whether a computer system is idle.
  • the process of determining whether the computer system is idle may be based on two or more characteristics of the computer system.
  • the two characteristics of the computer system may be GPU utilization and CPU utilization.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, and comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization and whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization. For instance, the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10% and whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%.
  • any two characteristics of the computer system may be used to determine whether a computer system is idle.
  • the process of determining whether the computer system is idle may be based on three characteristics of the computer system.
  • the three characteristics of the computer system may be GPU utilization, CPU utilization, and network utilization.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, and comparing an actual condition of the network utilization with a reference condition of the network utilization.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization, whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization, and whether an actual condition of the network utilization meets a reference condition of the network utilization. For instance, the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10%, whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%, and whether an actual condition of the network utilization meets a condition that the network utilization is less than about 5%.
  • the process of determining whether the computer system is idle may be based on four characteristics of the computer system.
  • the four characteristics of the computer system may be GPU utilization, CPU utilization, network utilization and mouse movement.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, and comparing an actual condition of a mouse movement with a reference condition of the mouse movement.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization, whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization, whether an actual condition of the network utilization meets a reference condition of the network utilization, and whether an actual condition of the mouse movement meets a reference condition of the mouse movement.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10%, whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%, whether an actual condition of the network utilization meets a condition that the network utilization is less than about 5%, and whether an actual condition of the mouse movement meets a condition that the mouse movement is less than about 5 pixels for at least about 3 minutes.
  • the process of determining whether the computer system is idle may be based on five characteristics of the computer system.
  • the five characteristics of the computer system may be GPU utilization, CPU utilization, network utilization, mouse movement, and keyboard input.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, comparing an actual condition of a mouse movement with a reference condition of the mouse movement, and comparing an actual condition of a keyboard input with a reference condition of the keyboard input.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization, whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization, whether an actual condition of the network utilization meets a reference condition of the network utilization, whether an actual condition of the mouse movement meets a reference condition of the mouse movement, and whether an actual condition of a keyboard input meets a reference condition of the keyboard input.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10%, whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%, whether an actual condition of the network utilization meets a condition that the network utilization is less than about 5%, whether an actual condition of the mouse movement meets a condition that the mouse movement is less than about 5 pixels for at least about 3 minutes, and whether an actual condition of a keyboard input meets a condition that the keyboard input is not detected for at least about 3 minutes.
  • the process of determining whether the computer system is idle may be based on six characteristics of the computer system.
  • the six characteristics of the computer system may be GPU utilization, CPU utilization, network utilization, mouse movement, keyboard input, and inactive period.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, comparing an actual condition of a mouse movement with a reference condition of the mouse movement, comparing an actual condition of a keyboard input with a reference condition of the keyboard input, and comparing an actual condition of an inactive period with a reference condition of the inactive period.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization, whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization, whether an actual condition of the network utilization meets a reference condition of the network utilization, whether an actual condition of the mouse movement meets a reference condition of the mouse movement, whether an actual condition of a keyboard input meets a reference condition of the keyboard input, and whether an actual condition of an inactive period meets a reference condition of the inactive period.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10%, whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%, whether an actual condition of the network utilization meets a condition that the network utilization is less than about 5%, whether an actual condition of the mouse movement meets a condition that the mouse movement is less than about 5 pixels for at least about 3 minutes, whether an actual condition of a keyboard input meets a condition that the keyboard input is not detected for at least about 3 minutes, and whether an actual condition of an inactive period meets a condition that the inactive period is between 18:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time).
  • the process of comparing an actual condition of an inactive period with a reference condition of the inactive period may be performed in a situation that actual conditions of GPU utilization, CPU utilization, network utilization, mouse movement, and/or keyboard input do not meet their respective reference conditions
  • the process of determining whether the computer system is idle may be based on seven characteristics of the computer system.
  • the seven characteristics of the computer system may be GPU utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period and runtime.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, comparing an actual condition of a mouse movement with a reference condition of the mouse movement, comparing an actual condition of a keyboard input with a reference condition of the keyboard input, comparing an actual condition of an inactive period with a reference condition of the inactive period, and comparing an actual condition of a runtime with a reference condition of the runtime.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization, whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization, whether an actual condition of the network utilization meets a reference condition of the network utilization, whether an actual condition of the mouse movement meets a reference condition of the mouse movement, whether an actual condition of a keyboard input meets a reference condition of the keyboard input, whether an actual condition of an inactive period meets a reference condition of the inactive period, and whether an actual condition of a runtime meets a reference condition of the runtime.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10%, whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%, whether an actual condition of the network utilization meets a condition that the network utilization is less than about 5%, whether an actual condition of the mouse movement meets a condition that the mouse movement is less than about 5 pixels for at least about 3 minutes, whether an actual condition of a keyboard input meets a condition that the keyboard input is not detected for at least about 3 minutes, whether an actual condition of an inactive period meets a condition that the inactive period is between 18:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time), and whether an actual condition of the runtime meets conditions of a previous runtime.
  • the conditions of a previous runtime may be previous actual conditions of the computer system during the previous runtime.
  • the previous actual conditions of the previous runtime may comprise previous idle states of the computer system during the previous runtime.
  • the process of comparing an actual condition of a runtime with a reference condition of the runtime may be performed in a situation that actual conditions of GPU utilization, CPU utilization, network utilization, mouse movement, keyboard input, and/or inactive period do not meet their respective reference conditions.
  • the process of determining whether the computer system is idle may be based on eight characteristics of the computer system.
  • the eight characteristics of the computer system may be GPU utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period, runtime and up-time.
  • the process of determining whether the computer system is idle may comprise comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, comparing an actual condition of a mouse movement with a reference condition of the mouse movement, comparing an actual condition of a keyboard input with a reference condition of the keyboard input, comparing an actual condition of an inactive period with a reference condition of the inactive period, comparing an actual condition of a runtime with a reference condition of the runtime, and comparing an actual condition of an up-time with a reference condition of the up-time.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a reference condition of the GPU utilization, whether an actual condition of the CPU utilization meets a reference condition of the CPU utilization, whether an actual condition of the network utilization meets a reference condition of the network utilization, whether an actual condition of the mouse movement meets a reference condition of the mouse movement, whether an actual condition of a keyboard input meets a reference condition of the keyboard input, whether an actual condition of an inactive period meets a reference condition of the inactive period, whether an actual condition of a runtime meets a reference condition of the runtime, and whether an actual condition of an up-time meets a reference condition of the up-time.
  • the process of determining whether the computer system is idle may comprise determining whether an actual condition of the GPU utilization meets a condition that the GPU utilization is less than about 10%, whether an actual condition of the CPU utilization meets a condition that the CPU utilization is less than about 20%, whether an actual condition of the network utilization meets a condition that the network utilization is less than about 10%, whether an actual condition of the mouse movement meets a condition that the mouse movement is less than about 5 pixels for at least about 3 minutes, whether an actual condition of a keyboard input meets a condition that the keyboard input is not detected for at least about 3 minutes, whether an actual condition of an inactive period meets a condition that the inactive period is between 18:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time), whether an actual condition of the runtime meets conditions of a previous runtime, and whether an actual condition of an up-time meets a reference condition of the up-time.
  • the process of comparing an actual condition of an up-time with a reference condition of the up-time may be performed in a situation that actual conditions of GPU utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period, and/or runtime do not meet their reference conditions.
  • An idle ledger may be used to determine whether the actual conditions meet with the respective reference conditions, and whether the computer system is idle. The value of the idle ledger may be increased if an actual condition meets a reference condition. The value of the idle ledger may be increased by any number if an actual condition meets a reference condition.
  • the value of idle ledger may be increased by 1, or any number; if an actual condition of the GPU utilization does not meet with a reference condition of the GPU utilization, the value of idle ledger may not be increased or may be changed by any number.
  • the value of idle ledger may be increased by 1, or any number; if an actual condition of the GPU utilization does not meet with a reference condition of the CPU utilization, the value of idle ledger may not be increased or may be changed by any number.
  • the value of idle ledger may be increased by 1, or any number; if an actual condition of the network utilization does not meet with a reference condition of the network utilization, the value of idle ledger may not be increased or may be changed by any number.
  • the value of idle ledger may be increased by 1, or any number; if an actual condition of the mouse movement does not meet with a reference condition of the mouse movement, the value of idle ledger may not be increased or may be changed by any number.
  • the value of idle ledger may be increased by 1, or any number; if an actual condition of the keyboard input does not meet with a reference condition of the keyboard input, the value of idle ledger may not be increased or may be changed by any number.
  • the value of idle ledger may be increased by 1.5 or any number; if an actual condition of the inactive period does not meet with a reference condition of the inactive period, the value of idle ledger may be increased by 0.5 or any number.
  • the value of idle ledger may be increased by 0.5 or any number; if an actual condition of the runtime does not meet with a reference condition of the runtime, the value of idle ledger may not be increased or may be changed by any number.
  • the value of idle ledger may be increased by 1, or any number; if an actual condition of the runtime does not meet with a reference condition of the runtime, the value of idle ledger may be increased by a value calculated from a formula or may be changed by any specific number. If the value is calculated from a formula, the value may be equal to l+(l-(runtime/expected runtime)).
  • the runtime in the equation may not be a historic runtime.
  • the initial value of the idle ledger may be zero.
  • the initial value of the idle ledger may not be zero.
  • the value of the idle ledger may be compared with a predetermined value to determine whether the computer system is idle.
  • the predetermined value may be any number set by the computer-implemented method. If the value of the idle ledger is larger than or equal to the predetermined value, then the computer system may be idle. If the value of the idle ledger is smaller than the predetermined value, then the computer system may not be idle.
  • two characteristics of the computer system GPU utilization and CPU utilization—ay be used to determine whether the computer system is idle. If an actual condition of the GPU utilization meets a reference condition of the GPU utilization, the value of idle ledger may be increased by 1. If the initial value of the ide ledger is 0, then the value of the idle ledger may be 1. And if an actual condition of the CPU utilization meets a reference condition of the CPU utilization, the value of idle ledger may be increased by 1, and the value of the idle ledger may be 2. If the predetermined value is 1.5, and the value of the idle ledger is 2, then the idle ledger is larger than the predetermined value. In this situation, the computer system may be idle because the value of the idle ledger is larger than the predetermined value.
  • FIG. 1 shows an example of a flowchart of a computer-implemented method for automatically processing data between a central repository, general ledger, distributed repository, distributed ledger,“proof of work” reward systems and/or hash algorithms with a computer system.
  • the computer-implemented method may first begin successful boot of hard drive operating system (“OS”), or runtime turnover 102.
  • the runtime turnover may be at most 24 hours, 23 hours, 22 hours, 21 hours, 20 hours, 19 hours, 18 hours, 17 hours, 16 hours, 15 hours, 14 hours, or smaller.
  • OS hard drive operating system
  • the computer-implemented method may initialize idle checking 104.
  • the computer-implemented method may also deactivate any active program if the program is running.
  • the active programs may be a miner software.
  • the computer-implemented method may aggregate previous actual conditions for last three runtimes 106.
  • the previous actual conditions of the characteristics of the computer system may be the previous actual condition of the GUP utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period, or any combination thereof.
  • the computer-implemented method may then proceed to a decision loop process 108.
  • the decision loop process may be repeated many times 109 until the value of the idle ledger is greater than a predetermined value.
  • the predetermined value may be 6.5. If the value of the idle ledger is greater than the predetermined value 111, meaning the computer system is idle, the miner software may be activated 112.
  • the computer-implemented method may monitor the mouse movement and/or keyboard input 114. If either mouse movement or keyboard input is detected, the computer-implemented method may deactivate the miner software and re-start to initialize/ idle checking 115.
  • FIG. 2 shows an example of a decision loop process of the computer-implemented method disclosed herein.
  • the computer-implemented method may first determine whether the actual condition of the mouse movement meets the reference condition of the mouse movement 202. If the actual condition of the mouse movement meets the reference condition of the mouse movement, the value of the idle ledger may be increased by 1. If the actual condition of the mouse movement does not meet with the reference condition of the mouse movement, the value of the idle ledger may not be increased. The computer-implemented method may then determine whether the actual condition of the keyboard input meets the reference condition of the keyboard input 204. If the actual condition of the keyboard input meets the reference condition of the mouse movement, the value of the idle ledger may be increased by 1.
  • the value of the idle ledger may not be increased.
  • the computer-implemented method may then determine whether the actual condition of the GPU utilization meets the reference condition of the GPU utilization 206. If the actual condition of the GPU utilization meets the reference condition of the GPU utilization, the value of the idle ledger may be increased by 1. If the actual condition of the GPU utilization does not meet with the reference condition of the GPU utilization, the value of the idle ledger may not be increased.
  • the computer-implemented method may then determine whether the actual condition of the CPU utilization meets the reference condition of the CPU utilization 208. If the actual condition of the CPU utilization meets the reference condition of the CPU utilization, the value of the idle ledger may be increased by 1. If the actual condition of the CPU utilization does not meet with the reference condition of the CPU utilization, the value of the idle ledger may not be increased.
  • the computer-implemented method may then determine whether the actual condition of the network utilization meets the reference condition of the network utilization 210. If the actual condition of the network utilization meets the reference condition of the network utilization, the value of the idle ledger may be increased by 1. If the actual condition of the network utilization does not meet with the reference condition of the network utilization, the value of the idle ledger may not be increased.
  • the computer-implemented method may then determine whether the actual condition of the inactive period meets the reference condition of the inactive period 212. If the actual condition of the inactive period meets the reference condition of the inactive period, the value of the idle ledger may be increased by 1.5. If the actual condition of the inactive period does not meet with the reference condition of the inactive period, the value of the idle ledger may not be increased.
  • the computer-implemented method may then determine whether the actual condition of the runtime meets the reference condition of the runtime 214. If the actual condition of the rune meets the reference condition of the runtime, the value of the idle ledger may be increased by 1. If the actual condition of the keyboard input does not meet with the reference condition of the runtime, the value of the idle ledger may not be increased.
  • the computer-implemented method may then determine whether the actual condition of the up-time meets the reference condition of the up-time 216. If the actual condition of the up-time meets the reference condition of the up time, the value of the idle ledger may be increased by 1. If the actual condition of the up-time does not meet with the reference condition of the up-time, the value of the idle ledger may be increased by a value calculated from a formula or may not be changed.
  • the computer-implemented method may then activate programs.
  • the programs may be third party programs.
  • the programs may not be third party programs.
  • the program can be any program executed using the resources of the computer system.
  • the programs may be installed in the computer system.
  • the programs may comprise any kind of software, for instance, but not limited to, game software, online service software, programming software, utility software, operating system software, browser software, word processor software, audio software, and video editing software.
  • the software can rely on structured computation, for example providing registration, segmentation and other functions, with the centrally-processed output made ready for downstream analysis.
  • the software may rely on unstructured computation, artificial intelligence or deep learning.
  • the software may rely on unstructured computation, such that data could be iteratively.
  • the programs may comprise miner software.
  • the miner software may comprise, but not limited to, HSRMiner - Neoscrypt Nvidia GPU Miner, XMR-Stak Miner - CPU & GPU for mining Monero (XMR) and AEON, MKXMiner Lyra2rev2 AMD GPUs (Vertcoin, Monacoin, Verge, STRAKS), Cast XMR - CryptoNight/CryptoNote Miner for RX Vega GPUs,
  • Cryptominer937's GUI Miners Current Support zPool, Ahashpool, NemosMiner - Multi Algo Profit Switching Nvidia Miner, CPUMiner-opt v3.8.0 - Open source optimized multi-algo CPU miner, CPUMiner (LucasJones & Wolf), Megaminer 5.2 - Multi pool / Multi Algo launcher, NHEQMiner - Open source & free CUDA ZEC, Siacoin GPU Miner, Marlin Siacoin Stratum Miner, GoMiner Official Decred Miner, SGMiner v5 - Optimized
  • the miner software may mine one or more cryptocurrencies with the computer system upon determining the computer system is idle.
  • the one or more cryptocurrencies may comprise, but not limited to, Bitcoin, Ethereum, Ripple, Bitcoin Cash, EOS, Litecoin, Cardano, Stellar, IOTA, NEO, Monero, Dash, NEM, TROn, Tether, VeChain, Ethereum Classic, Qtum,
  • Bioconductor BioJava, BioJS, BioMOBY, BioPeri, BioPHP, Biophython, BioRuby, EMBOSS, Galaxy, GenePattem, Geworkbench, GMOD, GenGIS, Genomespace, GENtile, Integrated Genome Browser, InterMine, LabKey Server, mother, PathVisio, Orange, Staden Package, Tavema workbench, ETGENE, ETnipept or any combination thereof.
  • the programs may use one or more hash algorithms.
  • the one or more hash algorithms may comprise, but not limited to SHA-256d, Scrypt, SHA-256, CryptoNote, NeoScrypt, 1CC/2CC/TWN, ECDSA, XI 1, RIPEMD160, CryptoNight, SHA3-512, Omnicore , PoS, xl7, Stellar Consensus Protocol (SCP) , Lyra2RE, Ethash, SHA-3, DPoS, Equihash, onixCoin, Genomics, pharmaceutical simulations, financial batch processing, lab sample analysis or any combination thereof.
  • the programs may be activated even when the computer system is not determined to be idle.
  • the value of the idle ledger may be less than the predetermined value, but only by a small amount.
  • the value of the idle ledger may be at least about 50%, 60%, 70%, 80%, 90% or greater than the predetermined value.
  • the programs may be activated but may only use a portion of the running power of the computer system.
  • the running power of the computer system may be related to the characteristics of the computer system. The portion may be at most 100%, 90%, 80%, 70%, 60% or less of the full running power of the computer system.
  • FIG. 3 shows an example of a block diagram of the system executing the computer-implemented method disclosed herein.
  • the system 300 may comprise a central operational control center (“COCC”) 302, one or more computer systems 304, a connection 306, and an external database 308.
  • the COCC 302 may manage remote activation settings.
  • the COCC 302 may monitor performance of at least one installed hardware.
  • the COCC 302 may send instructions to installed hardware about how to proceed when the computer system is idle.
  • the COCC 302 may comprise separate control software.
  • the COCC 302 may monitor the characteristics of the computer system 304 through a connection 306.
  • the COCC 302 may be in communication with the computer system 304 through the connection 306.
  • the COCC 302 may comprise one or more internal databases.
  • the COCC 302 may also use data from one or more external databases 308.
  • the reference conditions and the actual conditions of the characteristics of the computer system may be stored in the database.
  • the database may be a centralized database.
  • the database may be connected with one or more processors.
  • the one or more processors may analyze the data stored in the database through one or more algorithms.
  • the analysis performed by the one or more processors may include, but not limited to, calculating the value of the idle ledger for the up-time, comparing actual conditions with a plurality of reference conditions of the characteristics of the computer system, and determining whether the computer system is idle based on the actual conditions and the plurality of reference conditions.
  • the one or more processors may provide one or more instructions based on the analysis.
  • a database described herein may be accessed by one or more servers.
  • the connection may be a wired connection or wireless connection.
  • the COCC 302 and/or the computer system 304 may obtain data from the external database 308 through the connection 306.
  • the obtained data may be any information stored in the database.
  • the obtained data may be analyzed by the COCC.
  • the database can be stored in computer readable format.
  • a computer processor may be configured to access the data stored in the computer readable memory.
  • the COCC may comprise one or more servers.
  • the server may be in communication with the database.
  • the server may comprise known computing components, such as one or more processors, one or more memory devices storing software instructions executed by the processor(s), and data.
  • a server can have one or more processors and at least one memory for storing program instructions.
  • the one or more processors can be a single or multiple microprocessors, field programmable gate arrays (FPGAs), or digital signal processors (DSPs) capable of executing particular sets of instructions.
  • FPGAs field programmable gate arrays
  • DSPs digital signal processors
  • Computer-readable instructions can be stored on a tangible non-transitory computer-readable medium, such as a flexible disk, a hard disk, a CD-ROM (compact disk-read only memory), an MO (magneto-optical), a DVD-ROM (digital versatile disk-read only memory), a DVD RAM (digital versatile disk-random access memory), or a semiconductor memory.
  • a tangible non-transitory computer-readable medium such as a flexible disk, a hard disk, a CD-ROM (compact disk-read only memory), an MO (magneto-optical), a DVD-ROM (digital versatile disk-read only memory), a DVD RAM (digital versatile disk-random access memory), or a semiconductor memory.
  • the methods disclosed herein can be implemented in hardware components or combinations of hardware and software such as, for example, ASICs (application specific integrated circuits), special purpose computers, or general purpose computers.
  • Data connection established through the connection 306 may enables live connection between the COCC and the computer system so that the COCC can monitor environment
  • the computer system 304 may be client site computer system.
  • the client site computer system may comprise one or more personal computer hardware, the computer-implemented method installed on the client site computer system, and one or more connections connecting to the internet and the COCC.
  • the computer system 304 may comprise one or more electronic devices.
  • the number of electronic devices may be at least 1, 2, 3, 4, 5, 6, 7, 9, 10, or greater.
  • the electronic device may be mobile phones, PCs, tablets, printers, consumer electronics, and appliances.
  • the electronic device may be a portable electronic device.
  • the portable electronic device may comprise a user interface (UI), such as a graphical user interface (GUI).
  • the portable electronic device may be configured to communicate with the client site computer system to display the characteristics of the client site computer system.
  • the portable electronic devices may be wearable devices, including but not limited to, Fitbit, Apple watch, Samsung health, Misfit, Huawei Mi band, and Microsoft band.
  • the computer-implemented method may first establish connection between the computer system 304 and the COCC 302.
  • the connection 306 may be a wired connection or wireless connection.
  • wired communication components can include a Universal Serial Bus (USB) connection, a coaxial cable connection, an Ethernet cable such as a Cat5 or Cat6 cable, a fiber optic cable, or a telephone line.
  • Examples or wireless communication components can include a Wi-Fi receiver, a component for accessing a mobile data standard such as a 3G or 4G LTE data signal, or a Bluetooth receiver.
  • the COCC may send instructions to the computer system 304.
  • the COCC may exchange information with the computer system 304.
  • the instructions may include, but not limited to, initiating idle checking, detecting one or more characteristics of the computer system, comparing actual conditions with a plurality of reference conditions of the characteristics of the computer system, determining whether the computer system is idle based on the actual conditions and the plurality of reference conditions, and mining one or more cryptocurrencies with the computer system upon determining the computer system is idle.
  • the information may include, but not limited to, the actual conditions of the computer system 304,“idle” state check, uptime statistics (e.g. how long idle states has been in affect), cryptocurrency mining
  • the computer system 304 may then executed the computer-implemented method to determine whether the computer system is idle. If the computer system is idle, the status of the computer system may be transmitted back to COCC.
  • FIG. 4 shows an example of a client site computer system 400.
  • the client site computer system 400 may comprise a CPU 402.
  • the CPU 402 may perform the calculations, does the comparisons needed for processing, and/or controls the other parts of the personal computer.
  • the client site computer system may comprise a power supply 404.
  • the power supply 404 may convert standard electrical power into a form of the power that the computer system can use.
  • the client site computer system may comprise a fan 406.
  • the fan 406 may cool the CPU and any other components of the computer system.
  • the client site computer system may comprise a hard drive 408.
  • the hard drive 408 may store data and/or programs.
  • the hard drive 408 may be a principal storage device.
  • the client site computer system may comprise storage bays 410.
  • the storage bays 410 may hold storage devices, such as the floppy, DVD, and/or hard drives.
  • the client site computer system may comprise a DVD drive 412.
  • the DVD drive 412 may access data stored on CDs or DVDs.
  • the client site computer system may comprise a floppy drive 414.
  • the floppy drive 414 may access data stored on floppy disks.
  • the client site computer system may comprise memory slots 416.
  • the memory slots 416 may connect memory modules to the motherboard.
  • the client site computer system may comprise memory modules 418.
  • the memory modules 418 may store data temporality while the client is working with it.
  • the client site computer system may comprise motherboard 420.
  • the motherboard 420 may connect all components of the computer system.
  • the motherboard 420 may be the computer system’s main circuit board.
  • the client site computer system may comprise expansion slots 422.
  • the expansion slots 422 may connect expansion cards to the motherboard 420 to add additional capabilities.
  • the client site computer system may comprise expansion card 424.
  • the expansion card 424 may be used to connect peripheral devices and/or add new capabilities to a computer system.
  • FIG. 5 shows an example of a dashboard that is executed on a central operation control center (“COCC”).
  • the dashboard 500 may be presented on a screen of the COCC.
  • the dashboard may also be a graphical user interface (GUI) as part of an application that is executed on a mobile electronic device that operatively coupled with the COCC.
  • the mobile electronic device may comprise an electronic display screen (“screen”) for presenting the GUI.
  • the GUI may show an example of a program utilizing computing resources determined to be available by detecting idleness of a plurality of computer systems.
  • the program may comprise a mining software.
  • the GUI may provide real-time information about the available computing resources (e.g., idleness of a computer system) and the mining tasks assigned to these computing resources.
  • the dashboard 500 may comprise a plurality of graphical elements displayed on the screen.
  • the plurality of graphical elements may be icons.
  • the dashboard may include a first icon 502, a second icon 504, a third icon 506, a fourth icon 508, a fifth icon 510, and a sixth icon 512.
  • the first icon 502 may show a pool hashrate.
  • the pool hashrate may be a current or historic hashrate.
  • the second icon 504 may show an error rate and/or rejected rate. The error rate may be shown on the left side, and the rejected rate may be shown on the right side.
  • the third icon 506 may show a last share time. The details of the last share time may be shown by clicking a bar at the bottom of the third icon.
  • the fourth icon 508 may show a miner up-time. The details of the miner up-time may be shown at the bottom of the fourth icon.
  • the fifth icon 510 may show a status of the pool. The details of the status may be shown by clicking a bar at the bottom of the fifth icon.
  • the sixth icon 512 may show a temperature of the computer system. The details of the status may be shown at the bottom of the sixth icon.
  • the dashboard 500 may further comprise a miner detail table 514 positioned at the bottom of the dashboard.
  • the miner detail table may present information regarding a miner activity, including, but not limited to, the frequency, the shares, the last share, and the last share time.
  • the icons and the miner detail table may be mobile or may be fixed. Alternatively, the one or more of the icons and the miner detail table may be mobile (e.g., movable around the screen) or fixed in a single location.
  • the icons and the miner detailed table may be positioned at the top half of the screen, the bottom half of the screen, the top of the screen, the middle of the screen, or the bottom of the screen. If the icons and the miner detail table are presented on a mobile device, the icons and the miner detail table may be placed at a location that when a user is holding the device, all graphical elements are within reach of the user's thumb.
  • the plurality of icons may contain icons that each represents a description of a miner activity.
  • the description of the activity may be any type of information about a miner activity, including the name of the cryptocurrency mined, the frequency the cryptocurrency mined, the price of the cryptocurrency, and the change of the price of the cryptocurrency. Any number of icons may be displayed on the dashboard. Any description of the miner activity may be presented by an image, symbol, letter, number, shape, or any other type of visual representation of the activity of the client.
  • the icon may be shown in the shape of a rectangle.
  • the length or width of the rectangle of each icon may approximate the length of a user’s thumb, so that the tip of the user's thumb ergonomically aligns with the perimeter of the icon.
  • the outline of the rectangle may be shown in dot line, solid line, dash line, arrows, double lines, triple lines, or any combination of different types of lines.
  • the color of the outline of the rectangle may be gray, white, blue, red, or any color.
  • the outline of the rectangle may be colored by one visually obvious color, or two colors, with one color being visually more obvious than the other color.
  • any suitable shape can be used, such as a diamond, square, circle, etc.
  • the icons may have any shape, design, and/or size. Examples of possible shapes or designs include but are not limited to: regular shapes, irregular shapes, mathematical shapes, two-dimensional geometric shapes, curves, polygons, geometric shapes, shapes with metaphorical names, symbols, Unicode geometric shapes, shapes based on math symbols characters from any language history music art science religion, or any other form. Different descriptions of a miner activity may be represented by different shapes of icons.
  • FIG. 6 shows an example of a summary of a single miner showed on the screen of the COCC.
  • the summary 600 may be a graphical user interface (GUI) as part of an application that is executed on a mobile electronic device that operatively coupled with the central operation control center.
  • the mobile electronic device may comprise an electronic display screen
  • the summary 600 may comprise the overview of a singer miner.
  • the overview of a singer miner may comprise, but not limited to, hashrate, hardware errors, hardware error rate, uptime, software, accepted shares, rejected shares, stale shares, and discarded shares.
  • the summary 600 may comprise information regarding pools of a single miner.
  • the summary may comprise devices of a single miner.
  • FIG. 7 shows an example of a computer system 701 that is programmed or otherwise configured to execute the computer-implemented method disclosed herein.
  • the computer system 701 can regulate various aspects of method of the present disclosure, such as, for example, detecting a plurality of the characteristics of the computer system, determining whether the computer system is idle, and automatically starting to mine cryptocurrency.
  • the computer system 701 can be an electronic device of a user or a computer system that is remotely located with respect to the electronic device.
  • the electronic device can be a mobile electronic device.
  • the computer system 701 includes a central processing unit (CPU, also“processor” and“computer processor” herein) 705, which can be a single core or multi core processor, or a plurality of processors for parallel processing.
  • the computer system 701 can include memory or memory location 710 (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 715 (e.g., hard disk), communication interface 720 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 725, such as cache, other memory, data storage and/or electronic display adapters.
  • the memory 710, storage unit 715, interface 720 and peripheral devices 725 are in communication with the CPU 705 through a communication bus (solid lines), such as a motherboard.
  • the storage unit 715 can be a data storage unit (or data repository) for storing data.
  • the computer system 701 can be operatively coupled to a computer network (“network”) 730 with the aid of the communication interface 720.
  • the network 730 can be the Internet, an internet and/or extranet, or an intranet and/or extranet that is in communication with the Internet.
  • the network 730 in some cases is a telecommunication and/or data network.
  • the network 730 can include one or more computer servers, which can enable distributed computing, such as cloud computing.
  • the network 730, in some cases with the aid of the computer system 701 can implement a peer-to-peer network, which may enable devices coupled to the computer system 701 to behave as a client or a server.
  • the CPU 705 can execute a sequence of machine-readable instructions, which can be embodied in a program or software.
  • the instructions may be stored in a memory location, such as the memory 710.
  • the instructions can be directed to the CPU 705, which can subsequently program or otherwise configure the CPU 705 to implement methods of the present disclosure. Examples of operations performed by the CPU 705 can include fetch, decode, execute, and writeback.
  • the CPU 705 can be part of a circuit, such as an integrated circuit.
  • a circuit such as an integrated circuit.
  • One or more other components of the system 701 can be included in the circuit.
  • the circuit is an application specific integrated circuit (ASIC).
  • ASIC application specific integrated circuit
  • the storage unit 715 can store files, such as drivers, libraries and saved programs.
  • the storage unit 715 can store user data, e.g., user preferences and user programs.
  • the computer system 701 in some cases can include one or more additional data storage units that are external to the computer system 701, such as located on a remote server that is in communication with the computer system 701 through an intranet or the Internet.
  • the computer system 701 can communicate with one or more remote computer systems through the network 730.
  • the computer system 701 can communicate with a remote computer system of a user (e.g., user’s mobile phone).
  • remote computer systems include personal computers (e.g., portable PC), slate or tablet PC’s (e.g., Apple® iPad, Samsung® Galaxy Tab), telephones, Smart phones (e.g., Apple® iPhone, Android-enabled device, Blackberry®), or personal digital assistants.
  • the user can access the computer system
  • Methods as described herein can be implemented by way of machine (e.g., computer processor) executable code stored on an electronic storage location of the computer system 701, such as, for example, on the memory 710 or electronic storage unit 715.
  • the machine executable or machine readable code can be provided in the form of software.
  • the code can be executed by the processor 705.
  • the code can be retrieved from the storage unit 715 and stored on the memory 710 for ready access by the processor 705.
  • the electronic storage unit 715 can be precluded, and machine-executable instructions are stored on memory 710.
  • the code can be pre-compiled and configured for use with a machine having a processer adapted to execute the code, or can be compiled during runtime.
  • the code can be supplied in a programming language that can be selected to enable the code to execute in a pre-compiled or as-compiled fashion.
  • aspects of the systems and methods provided herein can be embodied in programming.
  • Various aspects of the technology may be thought of as “products” or“articles of manufacture” typically in the form of machine (or processor) executable code and/or associated data that is carried on or embodied in a type of machine readable medium.
  • Machine-executable code can be stored on an electronic storage unit, such as memory (e.g., read-only memory, random-access memory, flash memory) or a hard disk.
  • “Storage” type media can include any or all of the tangible memory of the computers, processors or the like, or associated modules thereof, such as various semiconductor memories, tape drives, disk drives and the like, which may provide non-transitory storage at any time for the software programming. All or portions of the software may at times be communicated through the Internet or various other telecommunication networks. Such communications, for example, may enable loading of the software from one computer or processor into another, for example, from a management server or host computer into the computer platform of an application server.
  • another type of media that may bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links.
  • a machine readable medium such as computer- executable code
  • a tangible storage medium such as computer- executable code
  • Non-volatile storage media include, for example, optical or magnetic disks, such as any of the storage devices in any computer(s) or the like, such as may be used to implement the databases, etc. shown in the drawings.
  • Volatile storage media include dynamic memory, such as main memory of such a computer platform.
  • Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprise a bus within a computer system.
  • Carrier-wave transmission media may take the form of electric or electromagnetic signals, or acoustic or light waves such as those generated during radio frequency (RF) and infrared (IR) data communications.
  • RF radio frequency
  • IR infrared
  • Common forms of computer-readable media therefore include for example: a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any other optical medium, punch cards paper tape, any other physical storage medium with patterns of holes, a RAM, a ROM, a PROM and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave transporting data or instructions, cables or links transporting such a carrier wave, or any other medium from which a computer may read programming code and/or data.
  • the computer system 701 can include or be in communication with an electronic display 735 that comprises a user interface (UI) 740 for providing, for example, information regarding the mined cryptocurrency.
  • UI user interface
  • Examples of UFs include, without limitation, a graphical user interface (GUI) and web-based user interface.
  • Methods and systems of the present disclosure can be implemented by way of one or more algorithms.
  • an algorithm can be implemented by way of software upon execution by the central processing unit 705.
  • the algorithm can, for example, determining whether the computer system is idle or in a different condition.
  • Example 1 Determine whether the computer system is idle based on two characteristics of the computer system
  • the process of determining whether the computer system is idle comprised comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, and comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization.
  • the process of determining whether the computer system is idle comprised determining whether an actual condition of the GPU utilization met a condition that the GPU utilization was less than about 10% and whether an actual condition of the CPU utilization met a condition that the CPU utilization was less than about 20%.
  • the value of the idle ledger was increased.
  • the value of the idle ledge was set to be zero.
  • the predetermined value showing the computer system was idle was set to be 1.5.
  • the actual condition of the GPU utilization was less than about 10%, and the idle ledger was increased to 1.
  • the actual condition of the CPU utilization was less than about 20%, and the idle ledger was increased to 2.
  • the value of the idle ledger was 2, which was larger than the predetermined value 1.5.
  • the computer system was idle.
  • Example 2 Determine whether the computer system is idle based on five characteristics of the computer system
  • the process of determining whether the computer system is idle comprised comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, comparing an actual condition of a mouse movement with a reference condition of the mouse movement, and comparing an actual condition of a keyboard input with a reference condition of the keyboard input.
  • the process of determining whether the computer system is idle comprised determining whether an actual condition of the GPU utilization met a condition that the GPU utilization was less than about 10%, whether an actual condition of the CPU utilization met a condition that the CPU utilization was less than about 20%, whether an actual condition of the network utilization met a condition that the network utilization was less than about 5%, whether an actual condition of the mouse movement met a condition that the mouse movement was less than about 5 pixels for at least about 3 minutes, and whether an actual condition of a keyboard input met a condition that the keyboard input was not detected for at least about 3 minutes.
  • the value of the idle ledger was increased.
  • the value of the idle ledge was set to be zero.
  • the predetermined value of the idle ledger showing the computer system was idle was set to be 4.
  • the actual condition of the GPU utilization was less than about 10%, and the idle ledger was increased to 1.
  • the actual condition of the CPU utilization was less than about 20%, and the idle ledger was increased to 2.
  • the actual condition of the network utilization was less than about 5%, and the idle ledger was increased to 3.
  • the actual condition of the mouse movement was less than about 5 pixels for at least about 3 minutes, and the idle ledger was increased to 4.
  • the actual condition of a keyboard input was not detected for at least about 3 minutes, and the idle ledger was increased to 5.
  • the final value of the idle ledger was 5, which was greater than the predetermined value 4.
  • the computer system was idle.
  • Example 3 Determine whether the computer system is idle based on eight characteristics of the computer system
  • the process of determining whether the computer system is idle comprised comparing an actual condition of the GPU utilization with a reference condition of the GPU utilization, comparing an actual condition of the CPU utilization with a reference condition of the CPU utilization, comparing an actual condition of the network utilization with a reference condition of the network utilization, comparing an actual condition of a mouse movement with a reference condition of the mouse movement, comparing an actual condition of a keyboard input with a reference condition of the keyboard input, comparing an actual condition of an inactive period with a reference condition of the inactive period, comparing an actual condition of a runtime with a reference condition of the runtime, and comparing an actual condition of an up- time with a reference condition of the up-time.
  • the process of determining whether the computer system is idle comprised determining whether an actual condition of the GPU utilization met a condition that the GPU utilization was less than about 10%, whether an actual condition of the CPU utilization met a condition that the CPU utilization was less than about 20%, whether an actual condition of the network utilization met a condition that the network utilization was less than about 5%, whether an actual condition of the mouse movement met a condition that the mouse movement was less than about 5 pixels for at least about 3 minutes, whether an actual condition of a keyboard input met a condition that the keyboard input was not detected for at least about 3 minutes, whether an actual condition of an inactive period met a condition that the inactive period was between 18:00 ( Pacific Standard Time) and 6:00 ( Pacific Standard Time), whether an actual condition of the runtime met conditions of a previous runtime, and whether an actual condition of an up-time met a reference condition of the up-time.
  • the value of the idle ledger was increased.
  • the value of the idle ledge was set to be zero.
  • the actual condition of the GPU utilization was more than about 10%, and the idle ledger remained 0.
  • the actual condition of the CPU utilization was more than about 20%, and the idle ledger remained 0.
  • the actual condition of the network utilization was less than about 5%, and the idle ledger was increased to 1.
  • the actual condition of the mouse movement was less than about 5 pixels for at least about 3 minutes, and the idle ledger was increased to 2.
  • the actual condition of a keyboard input was not detected for at least about 3 minutes, and the idle ledger was increased to 3.
  • the actual condition of an inactive period was between 18:00 ( Pacific Standard Time) and 6:00 (Pacific Standard Time), and the idle ledger was increased to 4.5.
  • the actual condition of the runtime was not the same as three previous runtimes, and the idle ledger remained 4.5.
  • the actual condition of an up-time was the same as reference condition of the up-time based on the actual conditions of GPU utilization, CPU utilization, network utilization, mouse movement, keyboard input, inactive period, and/or runtime of a previous up-time, and the idle ledger was increased to 5.5.
  • the final value of the idle ledger was 5.5, which was smaller than the predetermined value 6.5. Thus, the computer system was not idle.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Debugging And Monitoring (AREA)

Abstract

La présente invention concerne un procédé mis en œuvre par ordinateur pour traiter automatiquement des données entre un référentiel central, un registre général, un référentiel distribué, un registre distribué, des systèmes de récompense de type "preuve de travail" et/ou des algorithmes de hachage avec un système informatique.
PCT/US2019/033510 2018-05-22 2019-05-22 Procédés et systèmes de traitement automatisé de données WO2019226765A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201862674870P 2018-05-22 2018-05-22
US62/674,870 2018-05-22

Publications (1)

Publication Number Publication Date
WO2019226765A1 true WO2019226765A1 (fr) 2019-11-28

Family

ID=68617271

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2019/033510 WO2019226765A1 (fr) 2018-05-22 2019-05-22 Procédés et systèmes de traitement automatisé de données

Country Status (1)

Country Link
WO (1) WO2019226765A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021138591A1 (fr) * 2020-01-03 2021-07-08 Battelle Memorial Institute Solutions de cybersécurité à chaîne de blocs
CN113721883A (zh) * 2021-11-01 2021-11-30 中科声龙科技发展（北京）有限公司 基于Equihash算法比较数据序号的方法、装置及系统
US11727120B2 (en) 2019-07-11 2023-08-15 Battelle Memorial Institute Blockchain cybersecurity solutions

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060070067A1 (en) * 2004-06-03 2006-03-30 Dell Products L.P. Method of using scavenger grids in a network of virtualized computers
US20090171855A1 (en) * 2000-03-30 2009-07-02 Hubbard Edward A Monitizing Network Connected User Bases Utilizing Distributed Processing Systems
US20100281095A1 (en) * 2009-04-21 2010-11-04 Wehner Camille B Mobile grid computing
US20120016796A1 (en) * 2009-09-30 2012-01-19 Zynga, Inc. Apparatuses, Methods and Systems for a Trackable Virtual Currencies Platform
US20150271183A1 (en) * 2014-03-18 2015-09-24 nTrust Technology Solutions Corp. Virtual currency system
US20160292672A1 (en) * 2015-03-31 2016-10-06 Nasdaq, Inc. Systems and methods of blockchain transaction recordation

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090171855A1 (en) * 2000-03-30 2009-07-02 Hubbard Edward A Monitizing Network Connected User Bases Utilizing Distributed Processing Systems
US20060070067A1 (en) * 2004-06-03 2006-03-30 Dell Products L.P. Method of using scavenger grids in a network of virtualized computers
US20100281095A1 (en) * 2009-04-21 2010-11-04 Wehner Camille B Mobile grid computing
US20120016796A1 (en) * 2009-09-30 2012-01-19 Zynga, Inc. Apparatuses, Methods and Systems for a Trackable Virtual Currencies Platform
US20150271183A1 (en) * 2014-03-18 2015-09-24 nTrust Technology Solutions Corp. Virtual currency system
US20160292672A1 (en) * 2015-03-31 2016-10-06 Nasdaq, Inc. Systems and methods of blockchain transaction recordation

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11727120B2 (en) 2019-07-11 2023-08-15 Battelle Memorial Institute Blockchain cybersecurity solutions
WO2021138591A1 (fr) * 2020-01-03 2021-07-08 Battelle Memorial Institute Solutions de cybersécurité à chaîne de blocs
CN113721883A (zh) * 2021-11-01 2021-11-30 中科声龙科技发展（北京）有限公司 基于Equihash算法比较数据序号的方法、装置及系统

Similar Documents

Publication Publication Date Title
Bidargaddi et al. Predicting which type of push notification content motivates users to engage in a self-monitoring app
US20210133632A1 (en) Systems and methods for model monitoring
CN110199302B (zh) 事件驱动的区块链工作流处理
Sengan et al. Markov mathematical analysis for comprehensive real-time data-driven in healthcare.
WO2019226765A1 (fr) Procédés et systèmes de traitement automatisé de données
US9117179B2 (en) Predicting user activity in social media applications
US20240214428A1 (en) Platform for management and tracking of collaborative projects
US20180247234A1 (en) Platform for management and tracking of collaborative projects
US11763201B1 (en) System and methods for model management
WO2014058933A2 (fr) Techniques pour présenter des informations d'événement à l'aide d'une visualisation de temporisation d'événement
Hsiao et al. OPIIoT: design and implementation of an open communication protocol platform for industrial internet of things
CN113505520A (zh) 用于支持异构联邦学习的方法、装置和系统
US20170093766A1 (en) User-Defined Notification Templates
US11977861B2 (en) Systems and methods for embedding a computational notebook
US9355481B2 (en) Dynamic visualization for optimization processes
US20150095875A1 (en) Computer-assisted release planning
WO2017074825A1 (fr) Gestion de processus au moyen de modèles tiers
CN110458398A (zh) 项目数据监控方法、服务器及存储介质
WO2020230154A1 (fr) Systèmes, procédés et produit-programme informatique de génération d'un flux de production pour un projet
US10127293B2 (en) Collaborative data intelligence between data warehouse models and big data stores
Hussain et al. Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare
Olson Can real-world evidence save pharma US $1 billion per year? A framework for an integrated evidence generation strategy
CN113971074A (zh) 事务处理方法、装置、电子设备及计算机可读存储介质
CN114092275A (zh) 企业经营异常监测方法、装置、计算机设备和存储介质
WO2019136178A1 (fr) Plate-forme de développement, déploiement et calibrage d'algorithmes collaboratifs

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19808073

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 25/03/2021)

122 Ep: pct application non-entry in european phase

Ref document number: 19808073

Country of ref document: EP

Kind code of ref document: A1