Exploiting self-organization and fault tolerance in wireless sensor networks: A case study on wildfire detection application

Autor(es)

Giuntini, Felipe Taliar ; Beder, Delano Medeiros ; Ueyama, Jo

• Tipo de documento: Artigo Científico
• Fonte: INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS; v. 13, n. 4, p. 16-pg., 2017-04-12.

Resumo

The wildfires caused by human occupation is one of the factors that most contributes to deforestation of conservation areas, resulting in a number of issues for ecological systems. Premature fire detections lead to the elimination or reduction of the damage that will be caused by a fire incident. Wireless sensor networks have been shown to be a good alternative for environmental monitoring applications, as they can collect and send information in real time, such as humidity, wind, and temperature of various parts of the forest. Due to problems such as power limitation, communication failure, and loss of nodes, the network topology is constantly changing, requiring mechanisms to achieve self-organization and fault tolerance. This article proposes the development of a model and application in self-organizing and fault-tolerant wireless sensor networks for fire detection in conservation areas. To achieve self-organization and fault tolerance, we rely on encouraged local interactions between neighboring nodes that monitor the same region and the coordination of tasks, through a supervisor node, equipped with a framework for developing component-based fault-tolerant applications. For the analysis and validation of both model and application, it was simulated 60 events in the network of sensors in a real scenario using the simulator Sinalgo. The results were classified as True (partial or absolute) or False (partial or absolute). In all, 45% of consensus identified a possible fault in the application and in only 35% there was absolute consensus. (AU)

• Processo FAPESP: 15/21642-6 - Provendo uma maior inteligência em IoTs: abordagens e aplicações em sensores, VANTs e smartphones
• Beneficiário: Jó Ueyama
• Modalidade de apoio: Auxílio à Pesquisa - Regular