TY - JOUR T1 - Target counting with Presburger constraints and its application in sensor networks. AU - Linker,Sven, AU - Sevegnani,Michele, Y1 - 2019/11/06/ PY - 2019/05/07/received PY - 2019/10/02/accepted PY - 2019/12/12/entrez PY - 2019/12/12/pubmed PY - 2019/12/12/medline KW - Presburger arithmetic KW - model enumeration KW - sensor networks KW - target counting SP - 20190278 EP - 20190278 JF - Proceedings. Mathematical, physical, and engineering sciences JO - Proc Math Phys Eng Sci VL - 475 IS - 2231 N2 - One of the applications popularized by the emergence of wireless sensor networks is target counting: the computational task of determining the total number of targets located in an area by aggregating the individual counts of each sensor. The complexity of this task lies in the fact that sensing ranges may overlap, and therefore, targets may be overcounted as, in this setting, they are assumed to be indistinguishable from each other. In the literature, this problem has been proven to be unsolvable, hence the existence of several estimation algorithms. However, the main limitation currently affecting these algorithms is that no assurance regarding the precision of a solution can be given. We present a novel algorithm for target counting based on exhaustive enumeration of target distributions using linear Presburger constraints. We improve on current approaches since the estimated counts obtained by our algorithm are by construction guaranteed to be consistent with the counts of each sensor. We further extend our algorithm to allow for weighted topologies and sensing errors for applicability in real-world deployments. We evaluate our approach through an extensive collection of synthetic and real-life configurations. SN - 1364-5021 UR - https://www.unboundmedicine.com/medline/citation/31824213/Management_of_acetaminophen_toxicity_a_review DB - PRIME DP - Unbound Medicine ER -