Tracking Biped Motion in Pervasive Environment

Textiles are ubiquitous to humans since ages. Transistors made of silicon have made a deep impact in modern industry. A new field of research called wearable electronics integrates both these worlds to provide intelligent new services. Based on modern technologies of textile manufacturing, a carpet is embedded with a network of computing devices. One of their applications is to sense, when someone walks over them. This carpet was used to track the path a person took on his walk. When a person steps on the carpet, embedded sensors in the carpet get activated. These activations are stored at a monitoring PC as a log file. This data is processed and carefully viewed by data mining algorithms to identify hidden patterns that reveal the trails of the subject on his motion over the carpet. Different methods for validating the data mining algorithms are presented. These methods are perfected to produce an ideal reference in a format that can be directly compared with the estimated results of the algorithms. The evaluation results show a better performance for the new approach compared to the state-of-the-art technologies. Veracious testing, discussions, suggestions and their impact after implementation, are discussed in detail. The concepts used in the data mining algorithms are structurally sound and maintainable. Suggestions are given for further work on this system as whole. The footsteps of the person walking on the carpet are identified. The trajectory of walk is traced. The carpet can be used in a variety of domains. Rich examples on usage, assisted with augmented literature conclude this work