SensEye: A multi-tier heterogeneous camera sensor network

• Main Author: Kulkarni, Purushottam
• Language: ENG
• Published: ScholarWorks@UMass Amherst 2007
• Subjects: Computer science
• Online Access: https://scholarworks.umass.edu/dissertations/AAI3254905

Rapid technological developments in sensing devices, embedded platforms and wireless communication technologies, have enabled and led to a large research focus in sensor networks. Traditional sensor networks have been designed as networks of homogeneous sensor nodes. Single-tier networks consisting of homogeneous nodes achieve only a subset of application requirements and often sacrifice others. In this thesis, I propose the notion of multi-tier heterogeneous sensor networks, sensors organized hierarchically into multiple tiers. With intelligent use of resources across tiers, multi-tier heterogeneous sensor networks have the potential to simultaneously achieve the conflicting goals of network lifetime, sensing reliability and functionality. I consider a class of sensor networks---camera sensor networks---wireless networks with image sensors. I address the issues of automatic configuration and initialization and design of camera sensor networks. Like any sensor network, initialization of cameras is an important pre-requisite for camera sensor networks applications. Since, camera sensor networks have varying degrees of infrastructure support and resource constraints a single initialization procedure is not appropriate. I have proposed the notions of accurate and approximate initialization to initialize cameras with varying capabilities and resource constraints. I have developed and empirically evaluated Snapshot, an accurate calibration protocol tailored for sensor network deployments. I have also developed approximate initialization techniques that estimate the degree of overlap and region of overlap estimates at each camera. Further, I demonstrate usage of these estimates to instantiate camera sensor network applications. As compared to manual calibration, which can take a long time (order of hours) to calibrate several cameras, is inefficient and error prone, the automated calibration protocol is accurate and greatly reduces the time for accurate calibration---tens of seconds to calibrate a single camera and can easily scale to calibrate several cameras in order of minutes. The approximate techniques demonstrate feasibility of initializing low-power resource constrained cameras with no or limited infrastructure support. With regards to design of camera sensor networks, I present the design and implementation of SensEye, a multi-tier heterogeneous camera sensor network and address the issue of energy-reliability tradeoff. Multi-tier networks provide several levels of reliability and energy usage based on the type of sensor used for application tasks. Using SensEye I demonstrate how multi-tier networks can achieve simultaneous system goals of energy efficiency and reliability.