Enabling Mobile Service Provision with Sensor Networks

Enabling Mobile Service Provision with Sensor Networks

Levent Görgü (University College Dublin, Ireland), Jie Wan (University College Dublin, Ireland), Gregory M.P. O’Hare (University College Dublin, Ireland) and Michael J. O’Grady (University College Dublin, Ireland)
DOI: 10.4018/978-1-4666-1981-4.ch011


Sensor infrastructures have been deployed in a variety of environments. Currently, many are fixed network configurations; however, Wireless Sensor Networks (WSNs) are likely to be predominant in the future as wireless technologies continue to evolve, facilitating greater transfer of data payloads such as wireless multimedia. Such a development offers new opportunities for innovative mobile services. For this to occur, there needs to be a greater convergence between conventional mobile computing platforms and sensor technologies, enabling service interoperability and integration. This is not an insurmountable difficulty. This chapter seeks how this issue can be addressed. It considers the state-of-the-art in pervasive sensing and mobile computing, explores the practical issue of engineering software solutions for mobile services that harness sensor components, and proposes a solution based on the intelligent agent paradigm.
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Towards Pervasive Sensing

Micro Electro-Mechanical Systems (MEMS) technology has proved fundamental in improving the capabilities of individual sensor nodes and hence sensor networks. Currently, regular sensor nodes and gateway (sink) nodes possess capabilities for communicating, data processing and enhanced sensing. Likewise, advances in nanotechnology have enabled the production of many types of chemical sensors. Such sensors are capable of continuously identifying and reporting a chemical concentration. The goal is to have small, inexpensive sensors that can be used in chemical analysis. Gas sensors for example, possess an ability to detect very small amounts of chemical elements in the environment. The use of wireless micro-sensors in sensor networks has generated a significant amount of interest in areas such as climate change research (Padhy et al. 2006), weather and tidal surge prediction (Osbourne et al. 2008), and intelligent buildings monitoring (Guestrin, Krause & Singh, 2005).

At present, many deployed sensor networks are static in nature. In such networks, mobility is generally not considered; however, there are many circumstances where mobility is important. Mobility may be considered under three perspectives (Ekici, Gu & Bozdag, 2006):

  • User Level Mobility: users accessing the information collected by the network may themselves be moving, for example, drivers accessing traffic and weather conditions.

  • Sensor Level Mobility: the sensors themselves may be moving, for example mobile robotic platforms (Howard, Mataric & Sukhatme, 2003; Liu et al. 2004).

  • Information Level Mobility: the event or object monitored by the network is mobile, for example surveillance (Jaynes, 2004).

Sensor networks may be loosely categorized as fixed or wireless.

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