Sensor Network for Structuring People and Environmental Information

Abstract

Recently numbers of studies have been performed to make robots behave and interact with people more friendly and effectively. For example, nonverbal human-like behaviors such as eye-contact or maintaining suitable distance are known to be important in forming social relationships with people To provide services effectively and behave humanlike, robots needs to obtain detailed information on where people exist or what they have been doing. Moreover, robots can provide services to people in two different ways: people find and approaches robots, or robots approach person that needs assistance. When we look for services in the current world, shops, information kiosks or wall maps in public spaces are typical examples of the first type. In order to receive the service, people need to find out where the service is provided and have to approach the place. On the contrary, there had been few examples for the second form. Lifeguards at the swimming pool may be a rare example. When someone drawn is found, s/he dives in to help the person. Although the latter form is much more convenient, why can they be rarely seen in our everyday life? This is because services of this form need monitoring and recognition of people requirements which is still a difficult task. However, with the progress in ubiquitous sensing systems, this convenient form of service is becoming real. Several research projects have been running under this intent. One typical example is the aware home However, due to the high cost required in building such system on individual houses, it is hard to imagine every home having these facilities. Instead, public space such as shopping malls, stations or airports are more likely to be equipped with these sensing systems. However, public spaces show typical natures that cannot be seen in individual homes such as: 1. they are typically crowded with people, 2. the area is wide, and 3. most of the places are designed for certain purpose. The first two shows that sensing is much more challenging in these places. But by the last feature, there is a 23 www.intechopen.com