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DEVELOPMENT OF A SELF-ADAPTING INTELLIGENT SYSTEM FOR BUILDING ENERGY SAVING AND CONTEXT-AWARE SMART SERVICES REPORTER: 戴邵賢 Author : Jinsung Byun and Sehyun.

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Presentation on theme: "DEVELOPMENT OF A SELF-ADAPTING INTELLIGENT SYSTEM FOR BUILDING ENERGY SAVING AND CONTEXT-AWARE SMART SERVICES REPORTER: 戴邵賢 Author : Jinsung Byun and Sehyun."— Presentation transcript:

1 DEVELOPMENT OF A SELF-ADAPTING INTELLIGENT SYSTEM FOR BUILDING ENERGY SAVING AND CONTEXT-AWARE SMART SERVICES REPORTER: 戴邵賢 Author : Jinsung Byun and Sehyun Park This paper appears in: Consumer Electronics, IEEE Transactions on Issue Date : February 2011 1

2 OUTLINE Introduction System Architecture Implementation Conclusion 2

3 INTRODUCTION(1) The researchers have recently focused on smart services and novel applications using an intelligent sensor. Examples include a service that intelligently controls the LED light based on the user’s movement and the intensity of illumination sensed by smart sensors. Research on building energy saving and smart services through a context aware system has been conducted. 3

4 INTRODUCTION(2) Existing systems have several limitations: Centralized system architecture Fixed rule-based control A limited network lifetime due to a sensor node using a finite battery Self-adapting Intelligent System (SIS) efficient self-clustering sensor network (ESSN) node type indicator based routing (NTIR) 4

5 SYSTEM ARCHITECTURE(1/6) 5

6 SYSTEM ARCHITECTURE(2/6) 6 The PGC: provided to a user under a given situation The PM manages the generated patterns The SMC: Sensing Manager (SM) To receive the sensing data and specific events from the SIS Mining Manager (MM) It gathers the information from the Internet according to the user requests or the events caused by the variations in the user’s state and surroundings. The SDC: The SDC plays an important role in service creation, service decision, service execution, service configuration, and service management The correlates the current situation with the pattern in order to search for the appropriate pattern. The DM analyzes the current user’s situation and surroundings

7 SYSTEM ARCHITECTURE(3/6) Dynamic pattern generation (DPG) algorithm 7

8 SYSTEM ARCHITECTURE(4/6) The Self-adapting Intelligent Sensor (SIS) 8

9 Events/data sensed by each node are aggregated by H-SIS and then transmitted to the SIG The SIG then analyses the user’s state and environmental patterns from the transmitted events/data 9 SYSTEM ARCHITECTURE(5/6)

10 SYSTEM ARCHITECTURE(6/6) The Energy-efficient Self-clustering Sensor Network (ESSN) breakdown detection query (BDQ) node discovery query (NDQ) The interval of BDQ transmission is determined in accordance with the predefined (fixed) and dynamic levels. If a source node needs a route to a destination node, it broadcasts a route request packet (ROUTE_REQ) to its neighbors When the destination receives a number of ROUTE_REQs from same source address, it selects the ROUTE_REQ with the minimum-hop path and returns to the source node a route reply packet (ROUTE_REP) including the route presented in the ROUTE_REQ. 10

11 IMPLEMENTATION These service scenarios are implemented by interacting with our system and a smart phone. Building energy monitoring and control service using a smart phone: Consumer device control and management through the environmental information gathered by the SIS 11

12 IMPLEMENTATION 12

13 The results show that the power saving using our system with fixed-threshold-based control and with DPG and AMA is approximately 6-18% and 16-24% respectively, depending on the number of SISs. 13 IMPLEMENTATION ESSN-NTIR gradually decreases the slope of the service response time due to reduction in packet collision and packet loss. ESSN-NTIR enhanced the average number of packet transmissions, about 46% and 21%.

14 CONCLUSION Green IT technology used for sustainable growth is emerging The results show that the power saving using our system with DPG and AMA is approximately 16-24%, depending on the number of SISs. 14


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