Intelligent Energy Conservation
System Design Based on Hybrid
Wireless Sensor Network
Mr. chairman , Ladies and gentlemen. Good afternoon everyone . Thank you very much, Mr. chairman,for your kind introduction. 点明主题：
My topic today will deal with one of the most serious problems we are facing energy crisis.
It is Intelligent Energy Conservation System Design Based on HybridWireless Sensor Network
分成三部分：
I would like to divide my talk into three parts: 1)background 2) recent results and analysis; 3)conclusions.
一、背景
1. Background
阐释背景：
Now, I think it would be best to start out by making some general comments on previous work in this area.
With limited territory, large population, and rare natural resource, China mostly depended on import to provide energy needs up-to 97%. To solve the energy shortage and green house problem, all nations reach to the common sense to positively promote energy-saving activity. To save the electrical energy we have to manage all the environmental parameters such as temperature, humidity, luminance, and quality of air in the living space and probably adjust all the power-consuming facilities dynamically.
From the description above, we attempt to design an intelligent energy conservation system with ontological information agent which is an intelligent agent technique proceeding data mining, events analysis, and quickly response system. The system displays all the sensor information and environmental parameters on the server computer screen, and through the comparison between the real-time collected data with database to make decision and proceed feedback control to all power-consuming
facilities. Finally, the system is built in a campus building as a target for the effectiveness evaluation of the intelligent energy conservation system.
二、过程分析结果
1.Design Concept of Intelligent Energy conservation System
The energy conservation system could collect all the environmental parameters in an energyconsumption space such as room, house, office, factory, community, or any space. The collected parameters which include number of people, light luminance, temperature, power usage, and humidity would influence the operation strategy of the energy conservation system. These parameters are sent to middle-way station through ZigBee and then to server computer through Ethernet. The server will decide the feedback control command based on the proposed ontological information agent for the purpose of energy conservation. The feedback control command is then sent to controlled facilities via middle-way station using Bluetooth wireless communication for the regulation of air quality, temperature, light luminance, and control of affair machines and facilities. The design concept is shown in Fig. 1. The sensors of
temperature, luminance, humidity, power usage in this energy conservation system are designed with modules to meet different situations of power consumption such as power system, lights, air conditioner, official affairs machines and facilities. The information streams use a large number of WSN technology so as to construct
an active and intelligent energy conservation system. All sensor modules are designed with microprocessor as the core of control system. Consumers could combine some certain modules to set up the energy conservation system case-by-case in their own need.
Based on the design concept, the system structure of the energy conservation system shown in Fig. 2 consists of four parts as follow:
2. Intelligent Information Processing and Decision Making In this research, an ontological information agent with solution integration and agent techniques for intelligent information processing is proposed, which not only helps the whole system find out proper and integrated processing results, but also supports proxy access of information solutions through a two-tier solution finding process 。The architecture involves two main modules, namely casebased reasoning (CBR) and solution predictor, and shows how it interacts with the system interface. The solution finder is designed to serve as the central control for making control strategy to effectively achieve the goal of energy conservation. To ensure that all the knowledge used in CBR andsolution prediction can be automatically generated, we have introduced a solution predictor into the system. They will be described in the subsequent subsections.
As stated above, the solution finder is a system control manager. After receiving a query from the interface system, it tries to produce an answer following a two-tier algorithm, which includes predicted solution retrieval, CBR, and solution integration. We briefly summarize this process here.
3. System Installation and Effectiveness Evaluation
In this study we select the Electrical Engineering and Information Building in our campus as a target for the effectiveness evaluation of the intelligent energy conservation system. The sensors have been located at experimental laboratory, computer classroom, huge offices, and conference rooms, where are mostly powerconsuming spaces. The ZigBee network is located in a scatted net domain
structure as shown in Fig. 4. There are totally three net domains in the 2nd floor of the building and each net domain has its own PAN ID.
We have practically located the ZigBee wireless sensors in different teaching laboratories or room spaces in which temperature and humidity sensors are mounted. In order not to generate abnormal data, the sensor nodes should avoid to locate too close to the outlet of air conditioner. The number of the located sensor nodes depends on the size of space area. In this study 40 sensor nodes provided with both temperature and humidity detection function are distributed into 3 ZigBee net domains as shown in Fig. 4. Since coordinator is responsible to receiving all environmental parameters transmitted from sensors nodes (end device) any
time, the power supply of coordinator directly uses civilian electricity. As for the end device, all the environmental parameters are sensed and sent to coordinator per 80 seconds. Once the parameters are sent out, the end devices would enter into sleep mode to save power consumption. Therefore, we adopt three No.3 batteries to provide the power supply for end device.
三、结论
Conclusion
The active intelligent energy conservation system is originally designed and implemented utilizing hybrid wireless network. The various environmental detection sensor modules are also constructed for collecting all environmental parameters. In order to effectively achieve the goal of energy conservation, a two-tier ontological information agent is built in back-end server to provide the system with intelligent control strategy. With the proposed agent, the optimal feedback control commands are decided and then delivered to control the power-consuming facilities. After practical operating the intelligent energy conservation system in a campus building for 4 whole months, total 22.44% electricity power is saved with the help of intelligent energy conservation system. The effectiveness of the intelligent energy conservation system with ontological information agent is encouraged.
Intelligent Energy Conservation
System Design Based on Hybrid
Wireless Sensor Network
Mr. chairman , Ladies and gentlemen. Good afternoon everyone . Thank you very much, Mr. chairman,for your kind introduction. 点明主题：
My topic today will deal with one of the most serious problems we are facing energy crisis.
It is Intelligent Energy Conservation System Design Based on HybridWireless Sensor Network
分成三部分：
I would like to divide my talk into three parts: 1)background 2) recent results and analysis; 3)conclusions.
一、背景
1. Background
阐释背景：
Now, I think it would be best to start out by making some general comments on previous work in this area.
With limited territory, large population, and rare natural resource, China mostly depended on import to provide energy needs up-to 97%. To solve the energy shortage and green house problem, all nations reach to the common sense to positively promote energy-saving activity. To save the electrical energy we have to manage all the environmental parameters such as temperature, humidity, luminance, and quality of air in the living space and probably adjust all the power-consuming facilities dynamically.
From the description above, we attempt to design an intelligent energy conservation system with ontological information agent which is an intelligent agent technique proceeding data mining, events analysis, and quickly response system. The system displays all the sensor information and environmental parameters on the server computer screen, and through the comparison between the real-time collected data with database to make decision and proceed feedback control to all power-consuming
facilities. Finally, the system is built in a campus building as a target for the effectiveness evaluation of the intelligent energy conservation system.
二、过程分析结果
1.Design Concept of Intelligent Energy conservation System
The energy conservation system could collect all the environmental parameters in an energyconsumption space such as room, house, office, factory, community, or any space. The collected parameters which include number of people, light luminance, temperature, power usage, and humidity would influence the operation strategy of the energy conservation system. These parameters are sent to middle-way station through ZigBee and then to server computer through Ethernet. The server will decide the feedback control command based on the proposed ontological information agent for the purpose of energy conservation. The feedback control command is then sent to controlled facilities via middle-way station using Bluetooth wireless communication for the regulation of air quality, temperature, light luminance, and control of affair machines and facilities. The design concept is shown in Fig. 1. The sensors of
temperature, luminance, humidity, power usage in this energy conservation system are designed with modules to meet different situations of power consumption such as power system, lights, air conditioner, official affairs machines and facilities. The information streams use a large number of WSN technology so as to construct
an active and intelligent energy conservation system. All sensor modules are designed with microprocessor as the core of control system. Consumers could combine some certain modules to set up the energy conservation system case-by-case in their own need.
Based on the design concept, the system structure of the energy conservation system shown in Fig. 2 consists of four parts as follow:
2. Intelligent Information Processing and Decision Making In this research, an ontological information agent with solution integration and agent techniques for intelligent information processing is proposed, which not only helps the whole system find out proper and integrated processing results, but also supports proxy access of information solutions through a two-tier solution finding process 。The architecture involves two main modules, namely casebased reasoning (CBR) and solution predictor, and shows how it interacts with the system interface. The solution finder is designed to serve as the central control for making control strategy to effectively achieve the goal of energy conservation. To ensure that all the knowledge used in CBR andsolution prediction can be automatically generated, we have introduced a solution predictor into the system. They will be described in the subsequent subsections.
As stated above, the solution finder is a system control manager. After receiving a query from the interface system, it tries to produce an answer following a two-tier algorithm, which includes predicted solution retrieval, CBR, and solution integration. We briefly summarize this process here.
3. System Installation and Effectiveness Evaluation
In this study we select the Electrical Engineering and Information Building in our campus as a target for the effectiveness evaluation of the intelligent energy conservation system. The sensors have been located at experimental laboratory, computer classroom, huge offices, and conference rooms, where are mostly powerconsuming spaces. The ZigBee network is located in a scatted net domain
structure as shown in Fig. 4. There are totally three net domains in the 2nd floor of the building and each net domain has its own PAN ID.
We have practically located the ZigBee wireless sensors in different teaching laboratories or room spaces in which temperature and humidity sensors are mounted. In order not to generate abnormal data, the sensor nodes should avoid to locate too close to the outlet of air conditioner. The number of the located sensor nodes depends on the size of space area. In this study 40 sensor nodes provided with both temperature and humidity detection function are distributed into 3 ZigBee net domains as shown in Fig. 4. Since coordinator is responsible to receiving all environmental parameters transmitted from sensors nodes (end device) any
time, the power supply of coordinator directly uses civilian electricity. As for the end device, all the environmental parameters are sensed and sent to coordinator per 80 seconds. Once the parameters are sent out, the end devices would enter into sleep mode to save power consumption. Therefore, we adopt three No.3 batteries to provide the power supply for end device.
三、结论
Conclusion
The active intelligent energy conservation system is originally designed and implemented utilizing hybrid wireless network. The various environmental detection sensor modules are also constructed for collecting all environmental parameters. In order to effectively achieve the goal of energy conservation, a two-tier ontological information agent is built in back-end server to provide the system with intelligent control strategy. With the proposed agent, the optimal feedback control commands are decided and then delivered to control the power-consuming facilities. After practical operating the intelligent energy conservation system in a campus building for 4 whole months, total 22.44% electricity power is saved with the help of intelligent energy conservation system. The effectiveness of the intelligent energy conservation system with ontological information agent is encouraged.