CN104597859A - Internet of things training platform - Google Patents
Internet of things training platform Download PDFInfo
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- CN104597859A CN104597859A CN201410443417.5A CN201410443417A CN104597859A CN 104597859 A CN104597859 A CN 104597859A CN 201410443417 A CN201410443417 A CN 201410443417A CN 104597859 A CN104597859 A CN 104597859A
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- 238000012549 training Methods 0.000 title claims abstract description 32
- 238000002474 experimental method Methods 0.000 claims abstract description 17
- 238000004088 simulation Methods 0.000 claims abstract description 17
- 238000012545 processing Methods 0.000 claims abstract description 15
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 28
- 238000005259 measurement Methods 0.000 claims description 18
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 14
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 14
- 239000001569 carbon dioxide Substances 0.000 claims description 14
- 239000000428 dust Substances 0.000 claims description 14
- 229910052760 oxygen Inorganic materials 0.000 claims description 14
- 239000001301 oxygen Substances 0.000 claims description 14
- 230000008878 coupling Effects 0.000 claims description 4
- 238000010168 coupling process Methods 0.000 claims description 4
- 238000005859 coupling reaction Methods 0.000 claims description 4
- 238000002955 isolation Methods 0.000 claims description 4
- 230000003287 optical effect Effects 0.000 claims description 4
- 230000006978 adaptation Effects 0.000 claims description 3
- 238000009529 body temperature measurement Methods 0.000 claims description 3
- 238000011161 development Methods 0.000 abstract description 5
- 230000007613 environmental effect Effects 0.000 abstract description 4
- 230000005540 biological transmission Effects 0.000 abstract description 3
- 238000012544 monitoring process Methods 0.000 abstract description 2
- 230000001953 sensory effect Effects 0.000 abstract description 2
- 238000012795 verification Methods 0.000 abstract description 2
- 238000000034 method Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000005286 illumination Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication
- G05B19/4186—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication by protocol, e.g. MAP, TOP
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B25/00—Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Automation & Control Theory (AREA)
- Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Theoretical Computer Science (AREA)
- Electrically Operated Instructional Devices (AREA)
Abstract
The invention discloses an internet of things training platform which comprises a basic control module, a sensor acquisition module, an internet of things simulation application control module, an internet of things simulation experiment box, a power accessory and a signal simulation accessory. The internet of things training platform has the advantages that an internet of things training platform system is an internet of things training teaching stand which is self-developed by students and teachers and integrates teaching, competition, industrial control and environmental monitoring development, and a new-concept comprehensive intelligent laboratory integrating interesting demonstration, scientific experiment and application development based on the internet of things is built by comprehensively using the technical characteristics of an internet of things in the aspects such as intelligent sensing, network transmission and intelligent processing. By combining teaching with practice, combining sensory experience with operational development and combining project assumption with practical verification, the operational ability of the students is improved, and practical experience is accumulated, so that teaching quality level is integrally improved.
Description
Technical field
The invention belongs to teaching experimental base technical field, be specifically related to a kind of Internet of Things training platform.
Background technology
Along with day by day enriching of the commodity that circulate on the market, the fields such as bar code scan technology is collecting and distributing in logistics, supermarket merchandise sales obtain extensive utilization.In prior art, most bar-code identification adopts one-dimension code, and the maximum data length of one-dimension code is generally no more than 15 bytes, and it only can identify commodity, and the description of other information needs the storage in computer data storehouse.And Quick Response Code has the information capacity of nearly 1408 bytes, be not previously provided with commodity profile storehouse and the place being not easy to network and being connected, Quick Response Code can record the information of one-dimension code quantity of information tens times, and therefore, Quick Response Code has started more and more to be used.Current Most students Internet of Things training platform is all independently cabinet, when mounting circuit or sensor, electric wire is all exposed outer or run through cabinet and be arranged in cabinet at cabinet, the exposed outward appearance affecting experiment table at cabinet outward, this mode mounting circuit is convenient, run through and be arranged in cabinet, although ensure that the outward appearance of cabinet, run through this mode and be unfavorable for that circuit is changed and maintenance.
And the weak effect of the integrated process data of existing Internet of Things training platform, student is on training platform during real training, only can be suitable for single experimental implementation, be not easy to group's experimental implementation, cause the collaboration capabilities or the individual's warfighting capabilities in all directions that are difficult to the team promoting student.Teacher can not check the experiment information of each practical traning platform on any computer, and the result of real training can not intuitively show.
Summary of the invention
The invention provides a kind of Internet of Things training platform, to solve the ability of the integrated process data of existing training platform, the result of real training shows not technical matters intuitively.
In order to solve above technical matters, the technical scheme that the present invention takes is:
A kind of Internet of Things training platform, described Internet of Things training platform comprises base control module, sensor acquisition module, Internet of Things simulation application control module, Internet of Things simulated experiment case, Power Supply fittings and signal imitation accessory, described base control module is connected by data line with described sensor acquisition module, and described base control module, Internet of Things simulation application control module, Power Supply fittings and signal imitation accessory are connected by data line with described Internet of Things simulated experiment case respectively.
Be preferably, described base control module comprises LFC core processing module, LDX acquisition module, LDM control module, LVX acquisition module, LCC serial ports stipulations processing module and LTC low-power consumption acquisition module, described LFC core processing module, LDX acquisition module, LDM control module, LVX acquisition module, is mutually connected in series between LCC serial ports stipulations processing module and LTC low-power consumption acquisition module.
Be preferably, described base control module comprises 7 expansion modules and 32 timers, and isolation method is Phototube Coupling.
Be preferably, the empty node of input type of described base control module digital quantity input characteristics comprises input, drain-source and source type.
Be preferably, described sensor acquisition module comprises Temperature Humidity Sensor, oxygen sensor, carbon dioxide sensor, dust sensor, optical sensor and barometric pressure sensor, the input voltage 24VDC of described Temperature Humidity Sensor, temperature measurement range temperature is 0-100 DEG C, moisture measurement range temperature is 0-100%RH, and output area is 4-20MA; The input voltage 24VDC of described light sensor, light exposure measurement scope is 1-100KLUX, light exposure measurement precision ± 5%; The input voltage 24VDC of described oxygen sensor, the measurement range 0-30% of oxygen, measuring accuracy < ± 3% of oxygen; The input voltage 24VDC of described carbon dioxide sensor, the measurement range 0-2000ppm of carbon dioxide, measuring accuracy < ± 3% of carbon dioxide; The input voltage 24VDC of described dust sensor, the measurement range 0-8.8 of dust thousand/liter, measuring accuracy < ± 3% of dust.
Be preferably, described Internet of Things simulation application control module comprises LED lamp module, DC fan, relay output lamp and electrically driven curtain.
Be preferably, described Power Supply fittings comprises power interface and the power adaptation line of 5V, 12V, 24V.
After employing technique scheme, Internet of Things training platform system of the present invention be student and teacher's self-developing go out to integrate impart knowledge to students, Internet of Things practice-training teaching platform that contest, industry control, environmental monitoring are developed, the technical characteristic of comprehensive use Internet of Things in Intellisense, Internet Transmission and Intelligent treatment etc., build concept brand-new integrate entertaining demonstration, scientific experiment, application and development, based on the comprehensive Development of intelligent laboratory of Internet of Things.By the combination of imparting knowledge to students and put into practice, sensory experience and the combination starting to develop, scheme imagine the combination with actual verification, improve the manipulative ability of student, accumulation practical experience, thus level of improving the quality of teaching on the whole.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the topology view of Internet of Things training platform of the present invention;
Embodiment
For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making other embodiments all obtained under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, Internet of Things training platform is made up of base control module 2, sensor acquisition module 1, Internet of Things simulation application control module 4, Internet of Things simulated experiment case 3, Power Supply fittings 5 and signal imitation accessory 6.Base control module 2 is connected by data line with sensor acquisition module 1, in the data input base control module 2 that sensor acquisition module 1 gathers.Wherein base control module 2, Internet of Things simulation application control module 4, Power Supply fittings 5 are connected by data line with Internet of Things simulated experiment case 3 respectively with signal imitation accessory 6, and Power Supply fittings 5 provides electric power supply for Internet of Things training platform.
Wherein base control module 2 comprises LFC core processing module, LDX acquisition module, LDM control module, LVX acquisition module, LCC serial ports stipulations processing module and LTC low-power consumption acquisition module, and LFC core processing module, LDX acquisition module, LDM control module, LVX acquisition module, is mutually connected in series between LCC serial ports stipulations processing module and LTC low-power consumption acquisition module.LFC core processing module is used for process and the transmission of data, LDX acquisition module is used for the collection of DC voltage and current, LDM control module is used for DO output/DI and gathers, LVX acquisition module is used for AC current-voltage collection, LCC serial ports stipulations processing module is used for RS232/RS485 communication, and LTC low-power consumption acquisition module is used for solar storage battery and powers.
The experiment porch software of base control module 2 comprises various module software for editing, the optimum configurations of various node, sensing data collection.
The arithmetic speed 0.2us of base control module 2; supply voltage is 24V DC/220V AC; and electric current when 24V exports is 400mA; expansion module quantity has 7; single-phase counter is 2200KHz; two-phase counter is 2100KHz, and timer number has 32, possesses cryptoguard and real-time clock function simultaneously.The communication speed 300-38400bps of integrated communication function, the empty node of input type of digital quantity input characteristics has input, drain-source, source type three types.Input voltage is 24VDC, allowed band 0VDC-36VDC, and isolation method is Phototube Coupling, and isolating withstand voltage is 2500/5000Vr.m.s.The output type of digital output characteristic is that relay exports, and output voltage is 24VDC, and common port rated current is 4A/10A, single node maximum current 500mA/3A, and isolation method is Phototube Coupling.Base control module 2 is for gathering and export the basic sensing data of Control release.
Sensor acquisition module 1 comprises Temperature Humidity Sensor, oxygen sensor, carbon dioxide sensor, dust sensor, optical sensor and barometric pressure sensor.
Temperature Humidity Sensor gathers temperature and the humidity of environment; Oxygen sensor gathers environmental oxygen levels; Carbon dioxide sensor gathers ambient carbon dioxide content; Dust sensor gathers environment dust content; Optical sensor gathers illumination brightness; Barometric pressure sensor gathers atmospheric pressure.
The input voltage 24VDC of Temperature Humidity Sensor, temperature measurement range temperature is 0-100 DEG C; Moisture measurement range temperature is 0-100%RH; Output area is 4-20MA.
The input voltage 24VDC of light sensor, light exposure measurement scope is 1-100KLUX, light exposure measurement precision ± 5%.
The input voltage 24VDC of oxygen sensor, the measurement range 0-30% of oxygen, measuring accuracy < ± 3% of oxygen.
The input voltage 24VDC of carbon dioxide sensor, the measurement range 0-2000ppm of carbon dioxide, measuring accuracy < ± 3% of carbon dioxide.
The input voltage 24VDC of dust sensor, the measurement range 0-8.8 of dust thousand/liter, measuring accuracy < ± 3% of dust.
Be that DC5V, 12V, 24V, AC 220V power supply exports in Internet of Things simulation test case 3, DO/DI signal imitation, AI analog output, current/voltage definite value exports.
Internet of Things simulation application control module 4 comprises LED lamp module, DC fan, relay output lamp and electrically driven curtain.Wherein LED lamp module simulating chamber intraoral illumination, DC fan simulation fan, relay exports lamp simulation street lighting, and electrically driven curtain simulation household curtain, Internet of Things simulation application control module 4 controls for various kinds of equipment.
Power Supply fittings 5 comprises power interface and the power adaptation line of 5V, 12V, 24V, and Power Supply fittings 5 provides electric power supply for training platform.
Signal imitation accessory 6 and Internet of Things simulated experiment case 3 connecting analog various types of signal interface and corresponding fit line.
Sensor acquisition module 1 can every data of Real-time Collection data are inputed to base control module 2, the data processed through base control module 2 finally transfer to Internet of Things simulated experiment case 3, Internet of Things simulated experiment case 3 can show every data, thus experimental results can be understood in real time between teachers and students, and the data of experiment are cooperated.
Internet of Things training platform of the present invention is applicable to group or single experimental implementation, with the warfighting capabilities in all directions of the team collaboration's ability or individual that promote student.System adopts multilevel purview setting, and teacher can check the experiment information of each practical traning platform by any computer in net.Multiple environmental applications demo system can be simulated, promote students ' interest of study.Experiment completes, and can produce electronic report forms and laboratory report, and teacher can unify to consult written instructions.
Last it is noted that above embodiment only illustrates technical scheme of the present invention, be not intended to limit; Although with reference to previous embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein portion of techniques feature; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (7)
1. an Internet of Things training platform, it is characterized in that, described Internet of Things training platform comprises base control module, sensor acquisition module, Internet of Things simulation application control module, Internet of Things simulated experiment case, Power Supply fittings and signal imitation accessory, described base control module is connected by data line with described sensor acquisition module, and described base control module, Internet of Things simulation application control module, Power Supply fittings and signal imitation accessory are connected by data line with described Internet of Things simulated experiment case respectively.
2. Internet of Things training platform according to claim 1, it is characterized in that, described base control module comprises LFC core processing module, LDX acquisition module, LDM control module, LVX acquisition module, LCC serial ports stipulations processing module and LTC low-power consumption acquisition module, described LFC core processing module, LDX acquisition module, LDM control module, LVX acquisition module, is mutually connected in series between LCC serial ports stipulations processing module and LTC low-power consumption acquisition module.
3. Internet of Things training platform according to claim 2, is characterized in that, described base control module comprises 7 expansion modules and 32 timers, and isolation method is Phototube Coupling.
4. Internet of Things training platform according to claim 3, is characterized in that, the empty node of input type of described base control module digital quantity input characteristics comprises input, drain-source and source type.
5. Internet of Things training platform according to claim 4, it is characterized in that, described sensor acquisition module comprises Temperature Humidity Sensor, oxygen sensor, carbon dioxide sensor, dust sensor, optical sensor and barometric pressure sensor, the input voltage 24VDC of described Temperature Humidity Sensor, temperature measurement range temperature is 0-100 DEG C, moisture measurement range temperature is 0-100%RH, and output area is 4-20MA; The input voltage 24VDC of described light sensor, light exposure measurement scope is 1-100KLUX, light exposure measurement precision ± 5%; The input voltage 24VDC of described oxygen sensor, the measurement range 0-30% of oxygen, measuring accuracy < ± 3% of oxygen; The input voltage 24VDC of described carbon dioxide sensor, the measurement range 0-2000ppm of carbon dioxide, measuring accuracy < ± 3% of carbon dioxide; The input voltage 24VDC of described dust sensor, the measurement range 0-8.8 of dust thousand/liter, measuring accuracy < ± 3% of dust.
6. Internet of Things training platform according to claim 5, is characterized in that, described Internet of Things simulation application control module comprises LED lamp module, DC fan, relay output lamp and electrically driven curtain.
7. Internet of Things training platform according to claim 6, is characterized in that, described Power Supply fittings comprises power interface and the power adaptation line of 5V, 12V, 24V.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201410443417.5A CN104597859A (en) | 2014-09-02 | 2014-09-02 | Internet of things training platform |
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| CN201410443417.5A CN104597859A (en) | 2014-09-02 | 2014-09-02 | Internet of things training platform |
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| CN104597859A true CN104597859A (en) | 2015-05-06 |
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| CN201410443417.5A Pending CN104597859A (en) | 2014-09-02 | 2014-09-02 | Internet of things training platform |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10140147B2 (en) | 2017-02-16 | 2018-11-27 | Sanctum Solutions Inc. | Intelligently assisted IoT endpoint device |
| CN109658787A (en) * | 2017-10-12 | 2019-04-19 | 江南大学 | A kind of open source Internet of Things infrastest platform |
| CN112099363A (en) * | 2020-08-20 | 2020-12-18 | 广州市黄埔职业技术学校 | Real platform of instructing of thing networking simulation |
| RU2819568C1 (en) * | 2023-11-15 | 2024-05-21 | Федеральное государственное бюджетное образовательное учреждение высшего образования "Поволжский государственный университет телекоммуникаций и информатики" | Method of detecting training data for machine learning of computer system of industrial internet of things powered by rechargeable battery |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202650405U (en) * | 2012-05-24 | 2013-01-02 | 北京泛华恒兴科技有限公司 | Universal interface device and engineering teaching experiment system |
| WO2013123445A1 (en) * | 2012-02-17 | 2013-08-22 | Interdigital Patent Holdings, Inc. | Smart internet of things services |
| CN203179327U (en) * | 2013-01-18 | 2013-09-04 | 陆海空 | Integrated practical training platform for Internet of Things |
| CN103390364A (en) * | 2013-08-09 | 2013-11-13 | 哈尔滨理工大学 | Comprehensive experiment platform for electronic technology |
| CN103473964A (en) * | 2013-09-03 | 2013-12-25 | 无锡市七芯物联科技有限公司 | Comprehensive practical training platform used in teaching of Internet of things |
| CN203405976U (en) * | 2013-09-03 | 2014-01-22 | 无锡市七芯物联科技有限公司 | Ethernet teaching comprehensive training platform |
| CN203405997U (en) * | 2013-09-03 | 2014-01-22 | 无锡市七芯物联科技有限公司 | Ethernet education agricultural comprehensive training platform |
| CN204178209U (en) * | 2014-09-02 | 2015-02-25 | 宁波市蓝源物联科技有限公司 | A kind of Internet of Things training platform |
-
2014
- 2014-09-02 CN CN201410443417.5A patent/CN104597859A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013123445A1 (en) * | 2012-02-17 | 2013-08-22 | Interdigital Patent Holdings, Inc. | Smart internet of things services |
| CN202650405U (en) * | 2012-05-24 | 2013-01-02 | 北京泛华恒兴科技有限公司 | Universal interface device and engineering teaching experiment system |
| CN203179327U (en) * | 2013-01-18 | 2013-09-04 | 陆海空 | Integrated practical training platform for Internet of Things |
| CN103390364A (en) * | 2013-08-09 | 2013-11-13 | 哈尔滨理工大学 | Comprehensive experiment platform for electronic technology |
| CN103473964A (en) * | 2013-09-03 | 2013-12-25 | 无锡市七芯物联科技有限公司 | Comprehensive practical training platform used in teaching of Internet of things |
| CN203405976U (en) * | 2013-09-03 | 2014-01-22 | 无锡市七芯物联科技有限公司 | Ethernet teaching comprehensive training platform |
| CN203405997U (en) * | 2013-09-03 | 2014-01-22 | 无锡市七芯物联科技有限公司 | Ethernet education agricultural comprehensive training platform |
| CN204178209U (en) * | 2014-09-02 | 2015-02-25 | 宁波市蓝源物联科技有限公司 | A kind of Internet of Things training platform |
Non-Patent Citations (2)
| Title |
|---|
| 李建兵等: "物联网实训系统建设探析", 《实验科学与技术》 * |
| 顾卫杰等: "高职物联网综合实训平台的设计与开发", 《物联网技术》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10140147B2 (en) | 2017-02-16 | 2018-11-27 | Sanctum Solutions Inc. | Intelligently assisted IoT endpoint device |
| CN109658787A (en) * | 2017-10-12 | 2019-04-19 | 江南大学 | A kind of open source Internet of Things infrastest platform |
| CN112099363A (en) * | 2020-08-20 | 2020-12-18 | 广州市黄埔职业技术学校 | Real platform of instructing of thing networking simulation |
| RU2819568C1 (en) * | 2023-11-15 | 2024-05-21 | Федеральное государственное бюджетное образовательное учреждение высшего образования "Поволжский государственный университет телекоммуникаций и информатики" | Method of detecting training data for machine learning of computer system of industrial internet of things powered by rechargeable battery |
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Application publication date: 20150506 |