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Development of a Self-adapting Intelligent System for Building Energy Saving and Context-aware Smart Services. This paper appears in:  Consumer Electronics, IEEE Transactions on Issue Date :  February 2011 . Author : Jinsung Byun and Sehyun Park. Reporter: 戴邵賢. OutLine. Introduction

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Development of a Self-adapting Intelligent System for Building Energy Saving and Context-aware Smart Services

This paper appears in:  Consumer Electronics, IEEE Transactions onIssue Date :  February 2011 

Author : JinsungByun and Sehyun Park


  • Introduction
  • System Architecture
  • Implementation
  • Conclusion
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.
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)
system architecture 2 6
System Architecture(2/6)

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

system architecture 3 6
System Architecture(3/6)
  • Dynamic pattern generation (DPG) algorithm
system architecture 4 6
System Architecture(4/6)
  • The Self-adapting Intelligent Sensor (SIS)
system architecture 5 6
System Architecture(5/6)

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

system architecture 6 6
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.
  • 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

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.

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%.

  • 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.