Cognitive IoT system with intelligence techniques in sustainable computing environment

Forest border crossing animals creates major societal related issues, in addition to endangering their own lives. This is the objective focused in this paper targeting the species "The Elephant", incorporating with technical methodologies namely, mull-sensor data fusion, cognition theories and computational intelligence techniques. Mull-sensor data fusion provides three level detection of target, along with its related outputs, which improves performance metrics. Cognition theory resulted in obtaining other interesting features about the target. Computational intelligence techniques integrate and conclude the presence of the target in the pseudo-boundary. The technical combination enhances the novelty of the research work, resulting in achieving remarkable accuracy and minimized false alert. An IoT kit was designed and deployed in the real time wild environment in Hosur forest region for collecting the data of Elephant. Further, the notification is sent to the registered mobile of the forest authority, as an early warning for chasing the pachyderm back to the forest.