Efficient Distributed Localization Algorithm for Ownership Identification of Reindeer Calf Using Wireless Sensor Networks

Abstract

This paper presents a distributed algorithm for identifying the ownership of new-born reindeer calves using wireless sensor networks (WSNs). Reindeer are semi wild animals giving birth while in the wild. Although reindeer cows usually carry identification tags or signs of their owners, it is difficult to identify the ownership of the calves within a mixed herd. Currently, identification is performed in the traditional way which is stressful on both animals and herders and quite costly and time consuming. In this work, a localization algorithm implemented on a WSN is considered to get rid of matching mother reindeer to their calves in a fully automatic way. In particular, the proposed distributed localization algorithm is based on two phases where sensors nodes are attached to the reindeer in a confined space with the objective to identify the animals keeping close together the most of the time, which are reckoned to be the mother reindeer and her calf. At first, the initial estimated nodes’ positions are obtained from an existing biased-maximum likelihood estimator (B-MLE) based on the log-normal shadowing model (LNSM). Secondly, each sensor node seeks to estimate its local map (i.e., its own position and those from its neighbors) by using an on-line distributed stochastic approximation algorithm (DSA) such the identification mother-calves can be done. We present numerical are issued to the standard ZigBee IEEE 802.15.4 operating at 2:4 GHz by means of radio devices WSN430 (equipped with CC2420 chips).