Target counting with Presburger constraints and its application in sensor networks

Area of Science:

• Computer Science
• Electrical Engineering
• Network Systems

Background:

• Wireless sensor networks (WSNs) enable applications like target counting.
• Target counting in WSNs is complex due to overlapping sensor ranges and indistinguishable targets, leading to overcounting.
• Existing estimation algorithms lack guaranteed precision.

Purpose of the Study:

• To develop a novel, precise algorithm for target counting in WSNs.
• To provide guaranteed consistency between estimated counts and individual sensor counts.
• To extend the algorithm for real-world applicability with weighted topologies and sensing errors.

Main Methods:

• Developed a new target counting algorithm utilizing exhaustive enumeration of target distributions.
• Employed linear Presburger constraints for precise distribution analysis.
• Extended the algorithm to incorporate weighted topologies and sensing errors.

Main Results:

• The proposed algorithm guarantees that estimated counts are consistent with individual sensor counts.
• The algorithm demonstrates improved precision compared to existing methods.
• Evaluations were conducted using both synthetic and real-life configurations.

Conclusions:

• The novel algorithm offers a reliable solution for target counting in WSNs.
• Guaranteed precision and consistency are key advantages over current approaches.
• The algorithm's extensions enhance its practical utility in diverse deployment scenarios.