CN116126961A - Tamper-proof unattended weighing data system of regeneration circulation internet of things information system - Google Patents
Tamper-proof unattended weighing data system of regeneration circulation internet of things information system Download PDFInfo
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Abstract
The invention discloses a tamper-proof unattended weighing data system of a regenerative cycle internet of things information system, wherein a core data architecture of the tamper-proof unattended weighing data system is provided with an inner data architecture layer and an outer data architecture layer, the inner layer is constructed as a soft architecture guided by taking a data stream as a main body, and the outer layer is constructed as a hard architecture guided by taking a site array as a main body. The tamper-proof data system is used for storing and processing dynamic and serialized weighing data, and comprises the following data processing units according to the data construction process: a bottom layer dynamic data sequence unit; a dual random sequential data sequence unit; a scaled data encapsulation unit; other parallel hanging or subsequent development of data units. The invention further carries out deep development on the intellectualization, digitalization and visualization of recycling the circulating materials, develops and develops the unattended and tamper-proof automatic weighing subsystem at the bottom layer and the data construction thereof, and solves the problem of constructing the complete and autonomous data architecture on the intelligent internet of things chain.
Description
Technical Field
The invention relates to the technical field of regenerated industrial materials, in particular to a tamper-proof unattended weighing data system of a regenerated circulating internet of things information system.
Background
Along with the increasing consumption of resources and the increasing severity of environmental problems, the recycling of waste industrial materials not only shows more and more important values in technical industry and cost benefit, but also in higher and wider aspects such as social benefits, low carbon, environmental protection, energy conservation, emission reduction and other visual angle dimensions. In order to solve the problem of treatment of waste industrial materials, researchers have been exploring new technologies to improve the recycling rate of waste and reduce the environmental load. Worldwide, industrial waste recycling technology is continuously developed, and sustainable waste utilization modes are actively explored in various countries of the world. In recycling technology, some countries are leading, such as japan, the united states, germany, and the like, and have achieved good results in developing efficient waste recycling technology, and have certain reference and reference values. The field of regeneration and circulation of industrial waste materials is also continuously perfected and developed in China. In recent years, the government of China actively encourages waste recycling, and brings out related policies, and waste recycling management is enhanced. The recycling rate of industrial waste in China is obviously improved, and the recycling technology is continuously improved and perfected.
An important and obvious trend in the current state of the art is informatization, which promotes the progress of the waste recycling industry better through the application of information technology. No matter at home and abroad, along with the continuous development of informatization technology, the recycling of waste industrial materials is gradually moving to informatization and intellectualization.
Indeed, the informatization trend of recycled industrial materials has been related to various aspects of the whole industrial chain. For example, through the Internet and big data technology, the information collection, processing and management of the waste industrial materials can be performed in a digital mode, so that tracking, tracing, statistical analysis and the like of the waste industrial materials are realized. And the equipment such as the Internet of things technology and the intelligent sensor are used for cooperatively controlling, detecting and separating, and the like, so that the automatic sorting and processing of waste materials are realized, the refined recycling of waste materials and the efficient utilization of resources are realized, and the environmental pollution and the resource waste are reduced.
In particular, technologies such as intellectualization, digitization and visualization are also becoming the most attractive directions for recycling materials in the recycling industry, and the application of these new technologies can increase efficiency and convenience for recycling waste. For example, cloud management technology, which is rapidly developed in various industries, is used as an operation means of a highly integrated IT technology, and can easily track and supervise the whole waste recycling process, and can obtain real-time data and support. The intelligent waste recycling can be realized by the highly-digitized and vertically-customized internet of things, and the links such as data acquisition, transmission, analysis and processing in the recycling link can be automatically completed by the internet of things, so that the automatic identification, traceability and safety guarantee of the articles can be realized. The popularization of the AI technology promotes the digital upgrading in the field of waste recycling, and the development and the application of the AI not only can realize the rapid matching of important information such as waste identification and classification, but also can realize more accurate waste classification and recycling by continuously learning and improving an algorithm model. The introduction of the big data cloud computing technology enables the recycling of the waste to be clearly visualized, mass data is analyzed and processed by the big data cloud computing technology, the state of waste treatment and utilization can be more intuitively known through visualized data display, and the resource configuration and environmental protection evaluation process are optimized.
However, the informatization technology in the field of the regenerated industrial materials is still mainly embodied in detailed local application construction, mature data information modules and tools are directly introduced into the regeneration and recycling of industrial materials, and the technology is at a very beginning stage in China on the aspect of overall construction of a system, particularly in deep data model development.
Disclosure of Invention
The invention aims to solve the technical problem of developing an anti-tampering unattended weighing data system of a regenerated circulation internet of things information system based on the autonomous construction of an underlying unattended intelligent weighing data system.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows.
The tamper-proof unattended weighing data system of the regenerated circulation internet of things information system is used for storing and processing dynamic and serialized weighing data; the data system comprises the following data processing units according to the data construction process: a bottom layer dynamic data sequence unit; a dual random sequential data sequence unit; a scaled data encapsulation unit; other parallel hanging or subsequent development of data units.
As a preferred technical solution of the present invention, the data system comprises the following data processing units according to the data construction process: a bottom layer dynamic data sequence unit, which receives and generates a temporary data sequence based on the highest sampling frequency of the hardware device; the data unit is oriented to two differential data guides, namely (1) data redundancy elimination guide and (2) data safety enhancement guide, and the initial data sequence is subjected to double random generation; and the proportioned data packaging unit is used for carrying out data storage, transmission and restoration on the data sequence generated by the double random sequential data sequence unit and carrying out final packaging before characterization.
As a preferred technical solution of the present invention, the data system has a construction structure including: the bottom layer dynamic data sequence unit receives and generates a temporary data sequence based on the highest sampling frequency of the hardware equipment, and the temporary data sequence records a discrete data sequence in the whole process from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing according to a dynamic time sequence; data configuration is characterized as
；/>
、/>
The method respectively corresponds to the process time length from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing and the reciprocal of the highest sampling frequency of the weighing data in the dynamic process.
As a preferred technical solution of the present invention, the construction structure of the data system further includes: the dual random sequential data sequence unit is used for generating a procedural discrete data sequence of the bottom dynamic data sequence unit according to the highest sampling frequency of equipment, such as millisecond level and microsecond level, corresponding to a data array of one hundred magnitude to ten thousand magnitude, and is used for performing dual random generation on an initial data sequence in the direction of two differential data guides, namely (1) data redundancy elimination guide and (2) data safety enhancement guide; wherein the data guide (2) is an absolute dominant data guide, and the data guide (1) is a relative secondary auxiliary data guide; there are two data patterns for generating a double random data sequence in a double random sequential data sequence unit: A. the data guiding (1) and (2) correspond to the same double random data process, and the unique data process is adopted; B. the data guide (1) and (2) correspond to different double random data processes, and then the double random data process corresponding to the data guide (2) is adopted.
As a preferred technical solution of the present invention, the construction structure of the data system further includes: the scaling data packaging unit is used for completely characterizing real unattended automatic weighing data by a brand new data sequence generated by processing the double-random sequential data sequence unit, on one hand, the scaling data packaging unit comprises a discrete data sampling paradigm constructed by a bottom layer dynamic data sequence unit and data segmentation processing of the double-random sequential data sequence unit, so that the weighing data has basic safety attributes, and on the other hand, double randomness is reserved in the weighing data sequence by double randomness processing of the double-random sequential data sequence unit, and therefore, the real weighing data is stored, transmitted and restored and characterized by adopting the data sequence in the whole automatic traceable industrial chain, and the safety guarantee of the bottom layer data in the whole automatic weighing system is realized; the proportioned data packaging unit performs last packaging before data storage, transmission and restoration characterization on the data sequence generated by the double random sequential data sequence unit, and the data processing model is characterized by
The specific data processing paradigm is characterized as
I.e. with the random index in the first random data process +.>
And a random indicator in the second random data process +.>
Constructing a difference value between two adjacent dynamic weighting data on a non-uniform data sequence generated by a double random sequential data sequence unit, and marking the difference value as +.>
Meanwhile, the adjacent dynamic time difference corresponding to the dynamic pound difference is marked +.>
Sequentially progressively summarizing the initial bit data bits and adjacent data bits of the obtained randomized non-uniform data sequence to construct a dynamic proportioned data sequence on the whole randomized non-uniform data sequence; and the obtained data sequence is used as a terminal data sequence which contains real and single weighing data to carry out systematic storage, transmission and restoration characterization. The data processing process of the proportioned data packaging unit can be known, the derivative trend of dynamic data in the unattended automatic weighing process is represented to a certain extent, and the key point is that the dynamic derivative trend of weighing data is not changed along with the change of the weight of goods in general, which means that the data sequence obtained after proportioned packaging has the databased fault detection and tamper-proof properties besides meeting the safety, randomness and serialization requirements of the weighing data, namely, no matter the system or the human cause, when the data derivative trend represented by the obtained proportioned data sequence has larger deviation with the normal or standard data trend, the system data fault alarm or the human data tamper early warning is carried out; wherein the general or standard data trend may be manually calibrated, orBuilding a mean fitting of historical data; wherein the larger deviation is calibrated by human and allowed to be adjusted as needed.
As a preferred embodiment of the present invention, the data processing paradigm of the first random data process of the dual random sequential data sequence unit is characterized by
、
In the sequential interaction mode, data processing is performed according to +.>
Data paradigm +.>
Randomly splitting the whole process time length from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing from 100 to 1000, completing a complete randomization process in the sequential data definition, losing randomness in the second sequential data process, and corresponding to the random value, wherein the random value is the same as the random value of the electronic weighing equipment in single unattended weighing>
Middle->
The value of (a) is randomly obtained according to the first sequential processing>
Mapping values are carried out according to three known parameters +.>
、/>
And->
DeterministicObtaining; wherein (1)>
When the mapping is valued, the highest sampling frequency based on hardware equipment exists +>
Deriving the possibility that the value is a non-integer, selecting an integer value on both sides according to the principle of more proximity, e.g. +.>
The mapping value of (2) is 85.7, then +.>
=86; in the first random data process, two peer-to-peer data representation formats are constructed into sequential interaction modes, which is superior to the adoption of the advantages of clear logic and simple and accurate numerical operability>
The random value of the data is clear, the scale of data segmentation is represented in a scene mode,
directly act on->
On the contrary, according to->
The value is in the original w data sequence
The middle part is only required to be subjected to interval value, so that the intuitiveness and the easiness in executing the data operation are realized; the first random data process results in a two-level ordered data sequence of reduced order of magnitude compared to the underlying dynamic data sequence elements, which is oriented to two data guides, namely (1) data de-redundancy guide and (2) data security enhancement guide, which is represented by the enabling data support of the enabling & shaping data, for data de-redundancy guide, directly implemented by data order reduction, for data security enhancement guide, and is otherwise enabledThe implementation is performed through a random process. />
As a preferred technical scheme of the invention, the second random data process of the double random sequential data sequence unit adopts a data processing paradigm to further carry out secondary random enhancement of data security and realize proper reduction of data on the premise of keeping the sequential data sequence obtained by the first random data process, and in general, the data sequence generated by the first random data process still has order keeping property according to the original sampling data, and meanwhile, the data sequence generated by the first random data process is provided with the data sequence
The data interaction segmentation processing of the mode is a global data equipartition process, namely the obtained data sequence has equipartition property, and only the equipartition interval of the data is enlarged compared with that of the original sampling data; the data processing paradigm of the second random data process is characterized as
The method comprises the steps of carrying out a first treatment on the surface of the Wherein->
Sequentially progressive and at +.>
The internal random values are mapped onto the first random data sequence Cheng Suode in sequence so that the data interval number between the two sequential data corresponding to the ith time data mapping and the (i+1) time data mapping is->
The method comprises the steps of carrying out a first treatment on the surface of the Note that the sequential data and data intervals described herein are within the data sequence generated by the first random data process, and not within the data domain of the underlying dynamic data sequence unit;
corresponding make->
Is assigned to complete the process of first random dataThe assignment end point is reached after one single pass of the generated data sequence; thus, due to +.>
The new data sequence generated by the second random data process forms a randomized non-equipartition data sequence.
The beneficial effects of adopting above-mentioned technical scheme to produce lie in:
the invention has developed the intellectualization, digitalization and visualization of recycling the circulating materials deeply, especially the unmanned and tamper-proof automatic weighing subsystem and the data construction thereof which reside in the bottom core and foundation status, develop and develop the development, and solve the obstacle and the difficult problem in the construction of the complete autonomous self-contained core system and the data construction thereof for many years.
The detailed technical effects of the present invention are described in the following embodiments (examples 2 and 3). Specific details are set forth in the accompanying drawings, wherein the technical construction and details and the technical advantages thereof are described.
Detailed Description
In the following description of embodiments, for purposes of explanation and not limitation, specific details are set forth, such as particular system architectures, techniques, etc. in order to provide a thorough understanding of the embodiments of the application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail. It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Example 1, whole-Process informatization and traceable regeneration cycle Industrial chain Internet of things data System
On the whole framework, the whole informatization and traceable regeneration cycle industrial chain Internet of things data system comprises a guiding data framework with an inner layer and an outer layer, wherein the inner layer is constructed into a soft framework which is guided by taking data flows as main bodies, the soft framework comprises order data flows, goods data flows, ticket tax data flows, contract data flows, cash data flows and other data flows, and all the data flows are integrally data-co-linked and cooperated through an integrated data marking system taking the order flows as source carriers; the outer layer is constructed as a hard framework which takes the site array as a main body for guiding, and comprises an industrial renewable resource source end array, a recycling site array, an industrial renewable resource recycling and sorting array, a recycling resource reprocessing site array and a renewable resource finished product end user array, wherein each array is characterized by semantic data and/or digitized data.
Further: an intelligent weighing data module, a raw material finished product traceability data module, an intelligent warehouse-in and warehouse-out data module, a CRM (customer relationship management) and/or SRM (customer relationship management) data module and other data modules are built in the internet of things data system; the intelligent weighing data module is used for carrying out unattended automatic weighing on the renewable resources, carrying out encryption and tamper-proof processing through data processing, automatically transmitting weighing scales to the system and generating an online order; the raw material finished product traceability data module constructs a one-object one-code data channel, and accurately controls all links of the renewable resource co-production industry chain and can carry out whole traceability; the intelligent ex-warehouse data module constructs an ex-warehouse visual video database, expands a multi-site remote data array, and integrates big data of material data, work statistics, order data and anomaly monitoring of each site; the CRM and/or SRM data module is accessed into a mature management database, and the whole supply end and the whole application end are subjected to digital analysis and data arrangement.
In addition, in the aspect of functional conception and integration planning thereof, the tracing function of raw materials and finished products is aimed at tracing the source of raw materials, production and storage goods of the products, so that the whole life cycle tracing management of the products is realized, the source can be searched, the destination can be traced, the responsibility can be traced, and the cost can be controlled; the whole-process remote supervision function is directed to the blind spot aiming at information acquisition lag, high labor cost and the disjoint supervision of warehouse-in data, and is used for planning multi-site remote management, site business big data, employee work statistics, order abnormal monitoring and the like, carrying out real-time supervision, and being compatible with big data signboards, abnormal alarm, limited data sharing and the like; the intelligent warehouse-in and warehouse-out function guides management problems caused by order addition, realizes visual management of warehouse-in and warehouse-out, has clear inventory checking and updates data in real time; when the operation task is completed, the stock quantity is updated, so that the real account is consistent, the stock hysteresis and inaccuracy are avoided, the system automatically integrates the data of all links of the warehouse, forms related data reports, and the like, and radically solves the problems of disordered stock, disordered stock and the like of the traditional stock; CRM and SRM functions guide and improve the relation with customers on the supply chain and downstream, and internally cover customer management, provider management digitization, big data analysis, intelligent early warning, feeding and marketing and the like.
Example 2 tamper resistant unattended automatic weighing data System
In the embodiment, the informatization technology for the field of regenerated industrial materials is still mainly embodied in detailed local application construction (for example, mature data information modules and tools are directly introduced into the regeneration and recycling of industrial materials), but the situation of quite lacking in the whole construction of a system, especially in deep data model development, leads to various limitations of built-in software and data systems or outsourcing systems in the industry; therefore, the inventor technical team further carries out deep development on intellectualization, digitalization and visualization of recycling materials on the basis of previous development, and is compatible with advanced technologies such as polymer networking, AI identification, big data cloud computing and the like to create series products such as intelligent recycling, intelligent purchasing, unmanned on duty, intelligent warehouse-in and warehouse-out, operation monitoring, tracing and tracing, big data centers and the like. The development of unmanned and tamper-proof automatic weighing subsystem and data construction thereof, which reside in the bottom core and foundation, is especially conducted at present, so as to solve challenges and problems in the construction of a complete autonomous self-owned core system and data architecture thereof for many years.
The data development comprises two core guides of visualization and tamper resistance, the embodiment mainly comprises a guide of tamper resistance datamation, and the main body is constructed as an unattended tamper resistance weighing data subsystem of the whole-course informationized and traceable regeneration cycle industrial chain Internet of things data system in the embodiment 1. The construction structure of the data subsystem comprises:
1.1 underlying dynamic data sequence units.
The data unit receives and generates a temporary data sequence based on the highest sampling frequency of the hardware equipment, and the temporary data sequence records a discrete data sequence in the whole process from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing according to a dynamic time sequence; data configuration is characterized as
；/>
、/>
The method respectively corresponds to the process time length from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing and the reciprocal of the highest sampling frequency of the weighing data in the dynamic process. />
1.2 double random sequential data sequence units.
In the prior art, a procedural discrete data sequence of a bottom dynamic data sequence unit is generated according to the highest sampling frequency of equipment, such as millisecond and microsecond, and corresponds to a data array of one hundred magnitude to ten thousand magnitude, the dual random sequential data sequence unit faces two differential data guiding, namely (1) data redundancy elimination guiding and (2) data security enhancement guiding (the data guiding (2) is absolute dominant data guiding, the data guiding (1) is opposite secondary auxiliary data guiding, when the dual random data sequence is generated in the dual random sequential data sequence unit, two data patterns are respectively A and 2 correspond to the same dual random data process, the unique data process is adopted, and B and 2 correspond to different dual random data processes, and the dual random data process corresponding to the data guiding (2) is adopted, so that the initial data sequence is generated in a dual random mode.
1.2.1 characterization of data handling paradigm peering for the first random data procedure as
、/>
The two are selected independently or are interacted correspondingly in sequence, and in the sequential interaction mode, the data processing is carried out according to the first sequential data random process
Data paradigm +.>
Randomly splitting the whole process time length from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing from 100 to 1000, completing a complete randomization process in the sequential data definition, losing randomness in the second sequential data process, and corresponding to the random value, wherein the random value is the same as the random value of the electronic weighing equipment in single unattended weighing>
Middle->
The value of (a) is randomly obtained according to the first sequential processing>
Mapping values are carried out according to three known parameters +.>
、/>
And->
And obtaining certainty. />
When the mapping is valued, the highest sampling frequency based on hardware equipment exists +>
Deriving the possibility that the value is a non-integer, selecting an integer value on both sides according to the principle of more proximity, e.g. +.>
The mapping value of (2) is 85.7, then +.>
=86。
It can be seen that the two peer-to-peer data characterization paradigms are constructed as sequential interaction patterns during the first random data process, which has the advantage of being logically clear and numerically simple and accurate,
is characterized by the scale of data segmentation in a clear, episodic manner>
Directly act on->
On the contrary, according to->
The value is in the original w data sequence +.>
The method is characterized by being capable of taking values at intervals, and having intuitiveness and easiness in executing data operation.
The first random data process obtains a secondary sequential data sequence with order of magnitude reduced compared with the underlying dynamic data sequence unit, and the secondary sequential data sequence faces two data guides, namely (1) data redundancy elimination guide and (2) data security enhancement guide are shown as emboding & aforming data supportability, the data redundancy elimination guide is directly realized through data order reduction, and the data security enhancement guide is embodied through a random process.
1.2.2 the second random data Process employs the data processing paradigm to further perform a second random enhancement of data Security with an accompanying realization of appropriate reduction of data while maintaining the sequential data sequence derived from the first random data Process, and overall, the data sequence generated from the first random data Process is still ordered in terms of the original sampled data while it is
The data interaction segmentation processing of the mode is a global data equipartition process, namely the obtained data sequence has equipartition property, and only the equipartition interval of the data is enlarged compared with that of the original sampling data; the data processing paradigm of the second random data process is characterized by +.>
。
Wherein the method comprises the steps of
Sequentially progressive and at +.>
The internal random values are mapped onto the first random data sequence Cheng Suode in sequence so that the data interval number between the two sequential data corresponding to the ith time data mapping and the (i+1) time data mapping is->
. Note that the sequential data and data intervals herein are within the data sequence generated by the first random data process, and not within the data sequence of the underlying dynamic data sequence unit;
corresponding make->
Is performed on a single sequence of data generated by a first random data processThe assignment endpoint is reached after Cheng Bian calendar; thus, due to +.>
The new data sequence generated by the second random data process forms a randomized non-equipartition data sequence.
1.3 scaling the data encapsulation unit.
The brand new data sequence generated by the double-random sequential data sequence unit processing carries out complete characterization on real unattended automatic weighing data, on one hand, the brand new data sequence comprises a discrete data sampling paradigm constructed by a bottom dynamic data sequence unit and data segmentation processing of the double-random sequential data sequence unit, so that the weighing data has basic safety attributes, on the other hand, double randomness is reserved in the weighing data sequence by the double-random sequential data sequence unit, and therefore the real weighing data is stored, transmitted and restored and characterized by adopting the data sequence in the whole automatic traceable industrial chain, and the safety guarantee of the bottom-most data in the whole automatic weighing system is realized.
The proportioned data packaging unit performs last packaging before data storage, transmission and restoration characterization on the data sequence generated by the double random sequential data sequence unit, and the data processing model is characterized by
The specific data processing paradigm is characterized as
I.e. with the random index in the first random data process +.>
And a random indicator in the second random data process +.>
Constructing the difference between two adjacent dynamic weighting data on a non-uniform data sequence generated by a dual random sequential data sequence unitValue, marked->
Meanwhile, the adjacent dynamic time difference corresponding to the dynamic pound difference is marked +.>
Sequentially progressively summarizing the initial bit data bits and adjacent data bits of the obtained randomized non-uniform data sequence to construct a dynamic proportioned data sequence on the whole randomized non-uniform data sequence; and the obtained data sequence is used as a terminal data sequence which contains real and single weighing data to carry out systematic storage, transmission and restoration characterization.
The data processing process of the proportioned data packaging unit can be known, the derivative trend of dynamic data in the unattended automatic weighing process is represented to a certain extent, and the key point is that the dynamic derivative trend of weighing data is not changed along with the change of the weight of goods in general, which means that the data sequence obtained after proportioned packaging has the databased fault detection and tamper-proof properties besides meeting the safety, randomness and serialization requirements of the weighing data, namely, no matter the system or the human cause, when the data derivative trend represented by the obtained proportioned data sequence has larger deviation with the normal or standard data trend, the system data fault alarm or the human data tamper early warning is carried out; wherein the usual or standard data trend can be artificially calibrated or constructed by mean fitting of historical data; wherein the larger deviation is calibrated by human and allowed to be adjusted as needed.
Example 3 visual development (tamper-resistant unattended automatic weighing data subsystem internal development)
The method is used for visualizing the tamper-proof unattended automatic weighing data system, and the visualized development is mainly based on a weighing data subsystem with a hierarchical structure, and further comprises a video data subsystem with a dynamic node mark, wherein the video data subsystem is used for storing and processing unattended weighing video data.
Specifically, the method constructs the following data structure:
linear marker side dataset: constructing a homogenized linear dynamic node marking data sequence based on the highest sampling frequency of a hardware video device (allowed compatible objects include a video recording device, a storage device, a transmission device, a cloud server, a display device and the like), wherein the data sequence is used for dividing all video data recorded by the hardware device into node micro video fragments of different time nodes according to the highest possible frequency through linear marking mapping according to time sequence, thereby providing a data basis for subsequent video data retrieval, merging, playing, transmission, storage and other processing requirements;
random tag load data set: the method comprises the steps of hanging a random sequence database (a tamper-proof unattended automatic weighing data system in a weighing data subsystem) which is constructed in advance, carrying out data processing on node data corresponding to all the node micro video clips in the linear mark side data group one by one according to a data sequence in the random sequence database on the basis of the linear mark side data group, (because the data construction process of the linear mark side data group is embodied into data marks instead of physical and chemical video cutting, time selecting and section selecting video calling can be realized through addition and subtraction or combination operation of data mark points and subsequent data calling, and the application end presentation of video micro section cutting is achieved), and correspondingly realizing the time selecting section selecting, combining, playing, transmitting and storing of original video data.
It can be seen that the construction and description modes of the random marker loading data set can be directly loaded and adapted with the constructed random marker loading data set or the similar data set and the newly increased function expanding requirement thereof.
In other words, the data structure has infinite expansibility, can be applied to development and application of a plurality of subsequent functions (not limited to the weighing data subsystem and the regeneration material circulation system), and has obvious convenience advantages in logic and data construction and software function operation.
Example 4 visual tamper resistant unattended automatic weighing data System
The visual development is adaptively developed in the tamper-proof unattended automatic weighing data subsystem, and the embodiments 2 and 3 are directly integrated.
Specifically, the visual tamper-resistant unattended automatic weighing data system comprises a video data subsystem with dynamic node marks and a weighing data subsystem with a hierarchical structure on a data structure. The video data subsystem is used for storing and processing unattended weighting video data (embodiment 3), and the weighting data subsystem is used for storing and processing dynamic and serialized weighting data (embodiment 2).
Therefore, not only can the unattended automatic weighing be realized, but also the process video data can be called as required, the video call is realized through data operation instead of real video cutting while random adaptation, and the consumption of operation resources is almost zero and can be ignored.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments. In summary, each embodiment of the invention further develops intellectualization, digitalization and visualization of recycling materials deeply based on the prior development foundation by combining multiparty technical resources, and is compatible with advanced technologies such as polymer networking, AI identification, big data cloud computing and the like to create series products such as intelligent recycling, intelligent purchasing, unmanned on duty, intelligent warehouse-in and warehouse-out, operation monitoring, tracing and tracing, big data centers and the like.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (10)
1. Tamper-proof unattended weighing data system of regeneration circulation internet of things information system, which is characterized in that: the data system is used for storing and processing dynamic and serialized weighting data; the data system comprises the following data processing units according to the data construction process: a bottom layer dynamic data sequence unit; a dual random sequential data sequence unit; a scaled data encapsulation unit; other optional parallel hanging or subsequent development of data units.
2. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 1, wherein: the data system comprises the following data processing units according to the data construction process:
a bottom layer dynamic data sequence unit, which receives and generates a temporary data sequence based on the highest sampling frequency of the hardware device;
the data unit is oriented to two differential data guides, namely data redundancy elimination guide and data safety enhancement guide, and performs double random generation on an initial data sequence;
and the proportioned data packaging unit is used for carrying out data storage, transmission and restoration on the data sequence generated by the double random sequential data sequence unit and carrying out final packaging before characterization.
3. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 1, wherein: the construction structure of the data system comprises:
the bottom layer dynamic data sequence unit receives and generates a temporary data sequence based on the highest sampling frequency of the hardware equipment, and the temporary data sequence records a discrete data sequence in the whole process from a stable zero value to a stable highest value of the electronic weighing equipment in single unattended weighing according to a dynamic time sequence; data configuration is characterized as
；/>
、/>
Respectively corresponding to the process time length from a stable zero value to a stable highest value of electronic weighing equipment in single unattended weighing and the reciprocal of the highest sampling frequency of weighing data in the dynamic process;
the double-random sequential data sequence unit is used for carrying out double-random generation on an initial data sequence, wherein the processed discrete data sequence of the bottom dynamic data sequence unit is generated according to the highest sampling frequency of equipment, and the double-random sequential data sequence unit faces to two differential data guides, namely (1) data redundancy elimination guide and (2) data safety enhancement guide; wherein the data guide (2) is an absolute dominant data guide, and the data guide (1) is a relative secondary auxiliary data guide; there are two data patterns for generating a double random data sequence in a double random sequential data sequence unit: A. the data guiding (1) and (2) correspond to the same double random data process, and the unique data process is adopted; B. the data guiding (1) and (2) correspond to different double random data processes, and then the double random data process corresponding to the data guiding (2) is adopted;
the scaled data packaging unit performs last packaging before data storage, transmission and restoration characterization on the data sequence generated by the double random sequential data sequence unit, and the data processing model is characterized by
The specific data processing paradigm is characterized by +.>
I.e. with the random index in the first random data process +.>
Second random data procedureRandom index->
Constructing a difference value between two adjacent dynamic weighting data on a non-uniform data sequence generated by a double random sequential data sequence unit, and marking the difference value as +.>
Meanwhile, the adjacent dynamic time difference corresponding to the dynamic pound difference is marked +.>
Sequentially and progressively summarizing initial data bits and adjacent data bits of the data sequence obtained by the double-random sequential data sequence unit to construct a dynamic proportioned data sequence on the whole randomized non-uniform data sequence; and the obtained data sequence is used as a terminal data sequence which contains real and single weighing data to carry out systematic storage, transmission and restoration characterization. />
4. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 3, wherein: the dual random sequential data sequence unit performs dual random generation on an initial data sequence in a two-differential data direction (1) data redundancy elimination direction (2) data security enhancement direction, and specifically:
the data processing paradigm of the first random data process of the dual random sequential data sequence unit is characterized as
、/>
The two are selected independently or are interacted correspondingly in sequence, and in the sequential interaction mode, the data processing is carried out according to the first sequential data random process
Data paradigmThe lower->
Random segmentation from 100-1000 is carried out on the whole process time length from stable zero value to stable highest value of the electronic pound equipment in single unattended weighing, then complete randomization process is completed in the sequential data definition, and the randomness is lost in the second sequential data process, corresponding to the random value of the electronic pound equipment in single unattended weighing>
Middle->
Is randomly acquired according to the first sequential processing>
Mapping values are carried out according to three known parameters +.>
、/>
And->
Obtaining certainty; the first random data process obtains a two-level sequential data sequence of reduced order of magnitude compared to the underlying dynamic data sequence unit;
the second random data process of the double random sequential data sequence unit adopts a data processing paradigm to further carry out secondary random enhancement of data security and additionally realize data reduction on the premise of keeping the sequential data sequence obtained in the first random data process; the data processing paradigm of the second random data process is characterized as
The method comprises the steps of carrying out a first treatment on the surface of the Wherein->
Sequentially progressive and at +.>
The internal random values are mapped to the first random data sequence Cheng Suode in sequence, so that the data interval number between the two sequential data corresponding to the ith time data mapping and the (i+1) time data mapping is->
The method comprises the steps of carrying out a first treatment on the surface of the Note that the sequential data and data intervals described herein are within the data sequence generated by the first random data process, and not within the data domain of the underlying dynamic data sequence unit;
corresponding make->
The assignment end point is reached after completing one single pass traversal of the data sequence generated by the first random data process; thus, due to +.>
The new data sequence generated by the second random data process forms a randomized non-equipartition data sequence.
5. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 4, wherein: in the course of the first random data,
when the mapping is valued, the highest sampling frequency based on hardware equipment exists +>
The possible case where the derived value is a non-integer,at this time, an integer value on both sides is selected according to a more adjacent rule.
6. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 4, wherein: in the first random data process, two peer-to-peer data characterization paradigms are constructed as sequential interaction patterns,
is clear, the scale of the segmentation of the characterizing data of the scene, < >>
Directly act on->
On, according to->
The value is in the original w data sequence +.>
The interval value is taken, and the logic intuitiveness and the execution simplicity of the data operation are realized.
7. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 4, wherein: in the first random data process, the first random data process obtains a two-level sequential data sequence with order of magnitude reduced compared with the bottom dynamic data sequence unit, and the two-level sequential data sequence is oriented to two data guides, namely data redundancy elimination guide and data safety enhancement guide, wherein the data redundancy elimination guide is represented by the embedding and shaping data support, the data redundancy elimination guide is directly realized through the data order reduction, and the data safety enhancement guide is represented through the random process.
8. The tamper-resistant unattended pound count for a regenerative cycle internet of things information system according to claim 4According to the system, characterized in that: the data sequence generated by the first random data process has order-preserving property according to the original sampling data, and meanwhile
The data interaction segmentation processing of the mode corresponds to a global data equipartition process, and the obtained data sequence has equipartition property and is enlarged compared with the equipartition interval of the original sampling data.
9. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 4, wherein: in the course of the second random data,
the value is an integer.
10. The tamper-resistant unattended weighing data system of a regenerative cycle internet of things information system according to claim 4, wherein: in the course of the second random data,
the value range is an integer of 1-3. />
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