Grid-Based Orthogonal Cut algorithm for value-based multiple events localization in sensor networks

In this work, we improve the capability of spatial event localization in ad-hoc sensor networks equipped with simple sensor devices, in the context of smart camera networks. In our former work, the Orthogonal Cut approach has been used for that purpose. It is applicable in many different object localization scenarios without cooperation of the object and without much knowledge about the environment. It estimates the spatial position of a detected event by dividing the surveillance space of a sensor network into smaller areas until a threshold criterion is met. However that approach is limited to localization of a single object. In this paper, we extend the aforementioned algorithm for localization of multiple events (objects), introducing a Grid-Based Orthogonal Cut algorithm. This improved algorithm is able to detect and differentiate multiple objects within the same area, based on the strength of the sensed signal. We evaluate the performance of the algorithm and compare our algorithm with the solutions based on the individual sensor positions.