Teletraffic analysis of energy-efficient intruder detection using hash function techniques in images for remote monitoring in Wireless Sensor Networks. (October 2022) - Orea-Flores, Izlian Y.; Rivero-Angeles, Mario E.; Onofre-Soto, Ana L.; Azpeitia-Rebollar, Edna G.; Torres-Cruz, Noé; Villordo-Jiménez, Iclia; Pretelín-Ricárdez, Angel; Menchaca-Mendez, Rolando
Abstract: Many surveilling applications that use Wireless Sensor Networks (WSNs) are based on image transmissions to monitor relevant events like intruder detection. However, the continuous transmission of such images promptly drains the energy supply of nodes due to the large size of packets compared to other WSN-based applications such as temperature, gas leakages, and humidity, where packets are relatively small. In this work, we propose two techniques to reduce the packet size in image transmission data for outdoor surveillance. These techniques are based on obtaining a hash function of the histograms of images in different formats to transmit small-sized packets containing relevant information about the surveilled environment. If an event is detected, the complete images are transmitted to perform an in-depth inspection of the region of interest. Additionally, we propose an ON/OFF scheme to reduce energy consumption further. A teletraffic analysis is provided to evaluate the efficiency of such schemes for different environments. The derived mathematical model allows finely tuning the system variables to achieve both performance goals, which are usually in contraposition to each other, namely, increasing system lifetime and high detection probability.