CN112884302B - Electric power material management method - Google Patents
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- CN112884302B CN112884302B CN202110139234.4A CN202110139234A CN112884302B CN 112884302 B CN112884302 B CN 112884302B CN 202110139234 A CN202110139234 A CN 202110139234A CN 112884302 B CN112884302 B CN 112884302B
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- 239000000463 material Substances 0.000 title claims abstract description 31
- 238000007726 management method Methods 0.000 title abstract description 19
- 230000007613 environmental effect Effects 0.000 claims abstract description 70
- 230000002159 abnormal effect Effects 0.000 claims abstract description 13
- 238000004891 communication Methods 0.000 claims description 91
- 230000011218 segmentation Effects 0.000 claims description 28
- 230000002776 aggregation Effects 0.000 claims description 9
- 238000004220 aggregation Methods 0.000 claims description 9
- 238000000034 method Methods 0.000 claims description 7
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- 238000005265 energy consumption Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
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- 238000006467 substitution reaction Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention provides a power material management method, which comprises the following steps of S1, acquiring environmental parameters of a power material storage environment; s2, transmitting the environmental parameters to a cloud platform; and S3, judging whether the environmental parameters are abnormal or not by using a cloud platform, and if so, carrying out early warning prompt on the user. According to the invention, the environment parameters of the electric power material storage environment are acquired through the wireless sensor network, the environment parameters are transmitted to the cloud platform for processing, and early warning prompt is correspondingly carried out according to the processing result. The efficient management and the real-time management of the storage environment of the electric power materials are realized.
Description
Technical Field
The invention relates to the field of management, in particular to a power material management method.
Background
Daily storage management of electric power materials comprises warehouse management, storage management, warehouse-out management and the like. In the storage management link, the storage environment of the electric power materials is required to be managed, so that the electric power materials are prevented from being damaged due to unsuitable storage environment, in the prior art, people are generally dispatched to check the storage environment of the electric power materials regularly, but the mode is time-consuming and labor-consuming, low in efficiency and low in instantaneity.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a power material management method including:
s1, acquiring environmental parameters of an electric power material storage environment;
s2, transmitting the environmental parameters to a cloud platform;
and S3, judging whether the environmental parameters are abnormal or not by using a cloud platform, and if so, carrying out early warning prompt on the user.
Preferably, the acquiring the environmental parameters of the electric power material storage environment includes:
and acquiring environmental parameters of the electric power material storage environment by using the wireless sensor network.
Preferably, the environmental parameters include temperature, humidity and dust concentration.
Preferably, the wireless sensor network comprises a sensor node and a communication base station; the sensor node is used for acquiring the environmental parameters and transmitting the environmental parameters to a communication base station; the communication base station is configured to receive the environmental parameter.
Preferably, the transmitting the environmental parameter to the cloud platform includes:
the communication base station is also used for transmitting the environmental parameters to the cloud platform through a communication network.
Preferably, the determining, using a cloud platform, whether the environmental parameter is abnormal includes:
and the cloud platform judges whether the environmental parameters are in a preset numerical value interval, if so, the environmental parameters are normal, and if not, the environmental parameters are abnormal.
Preferably, the early warning prompting to the user includes:
after the cloud platform judges that the environmental parameters are abnormal, sending a judging result to a user terminal communicated with the cloud platform;
and after receiving the judging result, the user terminal sends out an early warning to the user.
Preferably, the sending the early warning to the user includes:
and sending an early warning to a user through popup windows or playing preset early warning sounds.
Preferably, the sensor nodes comprise a collection node and a collection node; the collecting node is used for acquiring the environmental parameters and transmitting the environmental parameters to the collecting node; the aggregation node is configured to transmit the environmental parameter to the communication base station.
Compared with the prior art, the invention has the advantages that:
according to the invention, the environment parameters of the electric power material storage environment are acquired through the wireless sensor network, the environment parameters are transmitted to the cloud platform for processing, and early warning prompt is correspondingly carried out according to the processing result. The efficient management and the real-time management of the storage environment of the electric power materials are realized.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a diagram illustrating an exemplary embodiment of a power material management method according to the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
As shown in the embodiment of fig. 1, the present invention provides a power material management method, which includes:
s1, acquiring environmental parameters of an electric power material storage environment;
s2, transmitting the environmental parameters to a cloud platform;
and S3, judging whether the environmental parameters are abnormal or not by using a cloud platform, and if so, carrying out early warning prompt on the user.
Preferably, the acquiring the environmental parameters of the electric power material storage environment includes:
and acquiring environmental parameters of the electric power material storage environment by using the wireless sensor network.
Preferably, the environmental parameters include temperature, humidity and dust concentration.
Preferably, the wireless sensor network comprises a sensor node and a communication base station; the sensor node is used for acquiring the environmental parameters and transmitting the environmental parameters to a communication base station; the communication base station is configured to receive the environmental parameter.
Acquiring environmental parameters through wireless sensor nodes has the following advantages:
the wireless sensor node is more convenient to set clearly compared with a wired sensor;
the installation is convenient, if a connecting line is arranged for each sensor node, the engineering quantity is huge, and the maintenance cost is high.
Preferably, the transmitting the environmental parameter to the cloud platform includes:
the communication base station is also used for transmitting the environmental parameters to the cloud platform through a communication network.
Preferably, the determining, using a cloud platform, whether the environmental parameter is abnormal includes:
and the cloud platform judges whether the environmental parameters are in a preset numerical value interval, if so, the environmental parameters are normal, and if not, the environmental parameters are abnormal.
The environment parameters are transmitted to the cloud platform, so that the storage environment of the electric power materials can be conveniently managed no matter where electric power material management personnel are located by utilizing the characteristic that the cloud platform can be connected across regions, for example, the temperature of a certain position can be checked.
Preferably, the early warning prompting to the user includes:
after the cloud platform judges that the environmental parameters are abnormal, sending a judging result to a user terminal communicated with the cloud platform;
and after receiving the judging result, the user terminal sends out an early warning to the user.
Preferably, the sending the early warning to the user includes:
and sending an early warning to a user through popup windows or playing preset early warning sounds.
Preferably, the sensor nodes comprise a collection node and a collection node; the collecting node is used for acquiring the environmental parameters and transmitting the environmental parameters to the collecting node; the aggregation node is configured to transmit the environmental parameter to the communication base station.
Preferably, the sensor nodes are divided into a sink node and a collector node by:
the communication base station periodically broadcasts a division instruction to the sensor node;
after receiving the broadcast instruction, the sensor node transmits own state data to the communication base station;
the communication base station divides the sensor nodes into a collection node and a collection node according to the state data.
Preferably, the dividing the sensor nodes into a collection node and a collection node according to the state data includes:
the communication base station acquires the minimum circumscribed rectangle of all the sensor node coverage areas;
and carrying out region division on the minimum circumscribed rectangle by using an iterative division mode:
the 1 st iteration, dividing the minimum circumscribed rectangle into 4 1 st generation sub-rectangles with the same area, respectively calculating the segmentation parameters of each 1 st generation sub-rectangle, and if the segmentation parameters are larger than a preset segmentation parameter threshold, the 1 st generation sub-rectangles participate in the 2 nd iteration segmentation;
the 2 nd iteration, divide the 1 st generation sub-rectangle that participates in this iteration to split into 4 2 nd generation sub-rectangles of equal area separately, and calculate the segmentation parameter of every 2 nd generation sub-rectangle separately, if the said segmentation parameter is greater than the preset segmentation parameter threshold value, the said 2 nd generation sub-rectangle participates in the 3 rd iteration to split;
similarly, the nth iteration divides the nth-1 generation sub-rectangle participating in the iterative segmentation into 4 nth-generation sub-rectangles with equal areas, calculates the segmentation parameter of each nth-generation sub-rectangle, and if the segmentation parameter is greater than a preset segmentation parameter threshold value, the nth-generation sub-rectangle participates in the n+1th iterative segmentation;
the segmentation parameters are calculated by the following way:
cuti＝α 1 ×numofb+α 2 ×aveE+α 3 ×sofb
where cuti represents the segmentation parameter, α 1 、α 2 、α 3 Representing a preset weight coefficient, numofb representing the number of sensor nodes contained in the sub-rectangle, aveE representing average remaining energy of the sensor nodes contained in the sub-rectangle, and softb representing the area of the sub-rectangle;
calculating the competition coefficient of each sensor node respectively:
wherein cmp represents the competition coefficient of the sensor node, a1, a2 and a3 represent preset weight coefficients, ejt represents the average communication hop count between the sensor node and the communication base station, b represents a preset control coefficient, midejt represents the average value of the average communication hop count between all the sensor nodes and the communication base station, leftE represents the residual energy of the sensor node, pE represents the average value of the residual energy of all the sensor nodes, tE represents a preset residual energy standard value, sp represents the data throughput rate of the sensor node in unit time, psp represents the average value of the data throughput rate of all the wireless sensor nodes in unit time, and tsp represents the standard value of the data throughput rate in unit time;
taking the finally obtained sensor node with the largest competition coefficient in the sub rectangle as a collecting node, and taking the rest sensor nodes in the sub rectangle as collecting nodes;
and determining a collection node for receiving the environmental parameters sent by the collection node according to a preset rule.
The distribution of the collecting nodes can be more uniform by dividing the coverage area of the sensor node into sub-rectangles and then dividing the collecting nodes and the collecting nodes. Specifically, the minimum circumscribed rectangle of the coverage area is divided in an iterative division mode, instead of directly dividing the minimum circumscribed rectangle into a plurality of sub-rectangles with the same area, so that the area of the sub-rectangles can be adjusted in a self-adaptive mode according to the distribution condition of the sensor nodes, and the distribution uniformity of the collection nodes is improved. When the competition parameter is calculated, parameters such as average communication hop count, residual energy, data throughput rate and the like and standard values corresponding to the parameters are considered, so that the competition parameter can comprehensively reflect the actual condition of the sensor node, and the sensor node which has small average communication hop count, more residual energy and high data throughput rate and is in communication base station is used as a collecting node in the sub rectangle, thereby ensuring the working efficiency and the working time of the collecting node.
Preferably, the determining, according to a predetermined rule, the sink node that receives the environmental parameter sent by the collecting node includes:
determining a set sU of the collection nodes in the communication range of the collection nodes;
calculating the advantage value of the mutual communication between the collection node and the collection node in the sU respectively:
where sn denotes a sink node in the sn, cn denotes a collection node, vco (cn, sn) denotes a dominant value of the mutual communication between sn and cn, eleft (sn) denotes a length of a straight line connection between sn and cn, dtb (sn) denotes a length of a straight line connection between sn and a communication base station, non (sn) denotes the number of collection nodes in a communication range of sn, r (sn) denotes a maximum communication distance of sn, mac (cn, sn) denotes a maximum data throughput between sn and cn in a unit time, and are (sn) denotes a total number of collection nodes in a communication range of sn for which an environmental parameter has been determined to be transmitted to sn; b1 and b2 represent weight parameters;
and if the collection node is out of the communication range of the collection node, selecting the collection node with the shortest straight line connection with the collection node as a sending target of the environmental parameters acquired by the collection node.
After the collection node is determined, the sending target of the environmental parameters acquired by the collection node is more reasonable. When the sending target is determined, not only the length of a straight line connecting between the collecting node and the collecting node, but also the maximum communication distance of the collecting node and the maximum data throughput in unit time are considered, and the number of the collecting nodes which send the environmental parameters to the collecting node is determined in the communication range of the collecting node, so that the condition that a single collecting node is responsible for the collection work of the environmental parameters sent by too many collecting nodes is avoided, the time period required for the environmental parameters to be transmitted from the collecting node to the collecting node is shortened, and the response speed of material management is improved.
Preferably, the aggregation node is configured to transmit the environmental parameter to the communication base station, and includes:
the aggregation node determines whether the communication base station is within its own communication range,
if yes, a communication mode between the communication base station and the communication base station is further selected, and then the environment parameters are sent to the communication base station through the finally selected communication mode;
if not, the environment parameters are sent to an intermediate node, and the intermediate node is used for transmitting the environment parameters to the communication base station;
the intermediate node is one of other aggregation nodes within the communication range of the aggregation node;
further selecting a communication mode between the communication base station and the communication base station, including:
the method comprises the steps that a collection node calculates the communication distance between the collection node and a communication base station, if the communication distance is larger than a set communication threshold, the collection node sends the environment parameters to the communication base station in a multi-hop communication mode, otherwise, the collection node sends the environment parameters to the communication base station in a single-hop communication mode;
the communication distance is calculated by:
cumd(sn,t+1)＝cumd(sn,t)-ti×t
where t represents a continuous operation time period of the sink node sn, cumd (sn, t+1) represents a communication distance between the sink node sn and the communication base station when the continuous operation time period is t+1, cumd (sn, t) represents a communication distance between the sink node sn and the communication base station when the continuous operation time period is t, ti represents a constant type parameter, perE (sn, t) represents an average energy consumption of transmission unit data between the sn and the communication base station during the operation time period t, dtb (sn) represents a length of a straight line connection between the sn and the communication base station, cE (sn) represents initial energy of the sn, xhE (sn, t) represents energy consumed by the sn during the operation time period t, and tb (sn) represents communication delay between the sn and the communication base station.
If the distance between the aggregation node and the communication base station is too large, the transmission of the environment parameters can be naturally performed only through the intermediate node. However, if the communication base station is within the communication range of the aggregation node, the communication base station may communicate with the communication base station in a single-hop or multi-hop manner. However, since the sink node located near the communication base station often serves as an intermediate node to transmit the environmental parameters transmitted from other sink nodes far away from the communication base station to the communication base station, if the sink node always uses a single-hop communication method to communicate with the communication base station, the amount of transfer data is too heavy, which definitely results in too fast consumption of energy, and thus the monitoring range cannot be guaranteed. Therefore, the communication distance parameter is designed, and along with the increase of the working time of the collection node, the communication distance value is smaller and smaller, so that the collection node is changed from single-hop communication to multi-hop communication, the distance for sending data by the collection node is reduced, the energy consumption of the collection node is reduced, and the working life of the collection node is prolonged.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (5)
1. A method of power material management, comprising:
s1, acquiring environmental parameters of an electric power material storage environment;
s2, transmitting the environmental parameters to a cloud platform;
s3, judging whether the environmental parameters are abnormal or not by using a cloud platform, and if so, carrying out early warning prompt on a user;
the obtaining the environmental parameters of the electric power material storage environment includes:
acquiring environmental parameters of an electric power material storage environment by using a wireless sensor network;
the wireless sensor network comprises sensor nodes and a communication base station;
the sensor node is used for acquiring the environmental parameters and transmitting the environmental parameters to a communication base station;
the communication base station is used for receiving the environment parameters;
the transmitting the environmental parameter to the cloud platform includes:
the communication base station is also used for transmitting the environmental parameters to a cloud platform through a communication network;
the sensor nodes comprise collecting nodes and collecting nodes;
the collecting node is used for acquiring the environmental parameters and transmitting the environmental parameters to the collecting node;
the aggregation node is used for transmitting the environment parameters to the communication base station;
the sensor nodes are divided into a collection node and a collection node by the following modes:
the communication base station periodically broadcasts a division instruction to the sensor node;
after receiving the broadcast instruction, the sensor node transmits own state data to the communication base station;
the communication base station divides the sensor nodes into a collection node and a collection node according to the state data;
the dividing the sensor nodes into a collection node and a collection node according to the state data comprises the following steps:
the communication base station acquires the minimum circumscribed rectangle of all the sensor node coverage areas;
and carrying out region division on the minimum circumscribed rectangle by using an iterative division mode:
the 1 st iteration, dividing the minimum circumscribed rectangle into 4 1 st generation sub-rectangles with the same area, respectively calculating the segmentation parameters of each 1 st generation sub-rectangle, and if the segmentation parameters are larger than a preset segmentation parameter threshold, the 1 st generation sub-rectangles participate in the 2 nd iteration segmentation;
the 2 nd iteration, divide the 1 st generation sub-rectangle that participates in this iteration to split into 4 2 nd generation sub-rectangles of equal area separately, and calculate the segmentation parameter of every 2 nd generation sub-rectangle separately, if the said segmentation parameter is greater than the preset segmentation parameter threshold value, the said 2 nd generation sub-rectangle participates in the 3 rd iteration to split;
similarly, the nth iteration divides the nth-1 generation sub-rectangle participating in the iterative segmentation into 4 nth-generation sub-rectangles with equal areas, calculates the segmentation parameter of each nth-generation sub-rectangle, and if the segmentation parameter is greater than a preset segmentation parameter threshold value, the nth-generation sub-rectangle participates in the n+1th iterative segmentation;
the segmentation parameters are calculated by the following way:
cuti＝α 1 ×numofb+α 2 ×aveE+α 3 ×sofb
where cuti represents the segmentation parameter, α 1 、α 2 、α 3 Representing a preset weight coefficient, numofb representing the number of sensor nodes contained in the sub-rectangle, aveE representing average remaining energy of the sensor nodes contained in the sub-rectangle, and softb representing the area of the sub-rectangle;
calculating the competition coefficient of each sensor node respectively:
wherein cmp represents the competition coefficient of the sensor node, a1, a2 and a3 represent preset weight coefficients, ejt represents the average communication hop count between the sensor node and the communication base station, b represents a preset control coefficient, midejt represents the average value of the average communication hop count between all the sensor nodes and the communication base station, leftE represents the residual energy of the sensor node, pE represents the average value of the residual energy of all the sensor nodes, tE represents a preset residual energy standard value, sp represents the data throughput rate of the sensor node in unit time, psp represents the average value of the data throughput rate of all the wireless sensor nodes in unit time, and tsp represents the standard value of the data throughput rate in unit time;
taking the finally obtained sensor node with the largest competition coefficient in the sub rectangle as a collecting node, and taking the rest sensor nodes in the sub rectangle as collecting nodes;
and determining a collection node for receiving the environmental parameters sent by the collection node according to a preset rule.
2. The method of claim 1, wherein the environmental parameters include temperature, humidity and dust concentration.
3. The method for managing electric power materials according to claim 1, wherein the determining whether the environmental parameter is abnormal using a cloud platform comprises:
and the cloud platform judges whether the environmental parameters are in a preset numerical value interval, if so, the environmental parameters are normal, and if not, the environmental parameters are abnormal.
4. A method of power material management according to claim 3, wherein the alerting the user comprises:
after the cloud platform judges that the environmental parameters are abnormal, sending a judging result to a user terminal communicated with the cloud platform;
and after receiving the judging result, the user terminal sends out an early warning to the user.
5. The method of claim 4, wherein the sending an alert to the user comprises:
and sending an early warning to a user through popup windows or playing preset early warning sounds.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005115569A (en) * | 2003-10-06 | 2005-04-28 | Matsushita Electric Works Ltd | Signal identification device and method |
| JP2008532324A (en) * | 2005-03-03 | 2008-08-14 | アプライド マテリアルズ インコーポレイテッド | Etching method with controlled processing result distribution |
| CN102036338A (en) * | 2010-12-22 | 2011-04-27 | 中国科学院计算技术研究所 | Sensor network real-time routing method based on data-driven link estimation |
| CN102176149A (en) * | 2011-02-24 | 2011-09-07 | 浙江工业大学 | Intelligent building energy consumption monitoring system based on wireless sensor network |
| KR20140029684A (en) * | 2012-08-29 | 2014-03-11 | 에스케이이노베이션 주식회사 | Systematic csma/ca transmission method for real-time mix traffic |
| CN104134217A (en) * | 2014-07-29 | 2014-11-05 | 中国科学院自动化研究所 | Video salient object segmentation method based on super voxel graph cut |
| CN106937352A (en) * | 2015-12-29 | 2017-07-07 | 扬州大学 | Mobile sink node Wireless Sensor Network Routing Protocol based on particle cluster algorithm |
| CN106954246A (en) * | 2017-05-19 | 2017-07-14 | 上海为然环保科技有限公司 | A kind of cloud application smart home with domestic electric network intelligent control function |
| CN107613578A (en) * | 2017-10-17 | 2018-01-19 | 上海潮旅信息科技股份有限公司 | A kind of microenvironment monitoring system based on wireless senser |
| WO2018143094A1 (en) * | 2017-02-02 | 2018-08-09 | 株式会社村田製作所 | Management node for wireless communication system, and wireless communication system |
| CN110213542A (en) * | 2019-06-06 | 2019-09-06 | 广州商学院 | A kind of comprehensive on-line monitoring cloud platform system of the foundation pit based on Internet of Things big data |
| CN110830945A (en) * | 2019-11-14 | 2020-02-21 | 南昌诺汇医药科技有限公司 | Intelligent substation monitoring system |
| CN111314473A (en) * | 2020-02-22 | 2020-06-19 | 洋浦美诺安电子科技有限责任公司 | Environmental monitoring system based on artificial intelligence |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106919582A (en) * | 2015-12-24 | 2017-07-04 | 阿里巴巴集团控股有限公司 | The association of network articles and related information statistical method and device |
-
2021
- 2021-02-01 CN CN202110139234.4A patent/CN112884302B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005115569A (en) * | 2003-10-06 | 2005-04-28 | Matsushita Electric Works Ltd | Signal identification device and method |
| JP2008532324A (en) * | 2005-03-03 | 2008-08-14 | アプライド マテリアルズ インコーポレイテッド | Etching method with controlled processing result distribution |
| CN102036338A (en) * | 2010-12-22 | 2011-04-27 | 中国科学院计算技术研究所 | Sensor network real-time routing method based on data-driven link estimation |
| CN102176149A (en) * | 2011-02-24 | 2011-09-07 | 浙江工业大学 | Intelligent building energy consumption monitoring system based on wireless sensor network |
| KR20140029684A (en) * | 2012-08-29 | 2014-03-11 | 에스케이이노베이션 주식회사 | Systematic csma/ca transmission method for real-time mix traffic |
| CN104134217A (en) * | 2014-07-29 | 2014-11-05 | 中国科学院自动化研究所 | Video salient object segmentation method based on super voxel graph cut |
| CN106937352A (en) * | 2015-12-29 | 2017-07-07 | 扬州大学 | Mobile sink node Wireless Sensor Network Routing Protocol based on particle cluster algorithm |
| WO2018143094A1 (en) * | 2017-02-02 | 2018-08-09 | 株式会社村田製作所 | Management node for wireless communication system, and wireless communication system |
| CN106954246A (en) * | 2017-05-19 | 2017-07-14 | 上海为然环保科技有限公司 | A kind of cloud application smart home with domestic electric network intelligent control function |
| CN107613578A (en) * | 2017-10-17 | 2018-01-19 | 上海潮旅信息科技股份有限公司 | A kind of microenvironment monitoring system based on wireless senser |
| CN110213542A (en) * | 2019-06-06 | 2019-09-06 | 广州商学院 | A kind of comprehensive on-line monitoring cloud platform system of the foundation pit based on Internet of Things big data |
| CN110830945A (en) * | 2019-11-14 | 2020-02-21 | 南昌诺汇医药科技有限公司 | Intelligent substation monitoring system |
| CN111314473A (en) * | 2020-02-22 | 2020-06-19 | 洋浦美诺安电子科技有限责任公司 | Environmental monitoring system based on artificial intelligence |
Non-Patent Citations (4)
| Title |
|---|
| "无线传感器网络QoS保障技术的研究";朱敬华;《中国优秀硕士学位论文全文数据库》;1-140 * |
| 基于粗糙C-均值聚类的能量均衡LEACH算法;严静静;张腾飞;;计算机工程(第12期);21-25 * |
| 基于蚁群的无线传感器网络能量均衡非均匀分簇路由算法;缪聪聪;陈庆奎;曹剑炜;章刚;;计算机应用(第12期);3410-3414 * |
| 无线传感器网络中移动sink节点的路径规划;柏琪;朱晓娟;;无线电通信技术(第02期);228-233 * |
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