The purpose of this paper is to perform large-scale environmental sensing with a lot of Internet of Things (IoT) devices, as typically seen in a Smart City, efficiently and for multiple applications. In this paper, we propose a novel sensing method, called mission-oriented sensing, which accepts multiple and dynamic sensing purposes on a single infrastructure.
The proposed method achieves the purpose by dealing sensing configuration (application’s purpose) as a mission. It realizes sharing single infrastructure by accepting multiple missions in parallel, and it accepts missions’ update anytime. In addition, the sensing platform based on military analogy can command and control a lot of IoT devices in good order, and this realizes mission-oriented sensing above.
Introducing mission-oriented sensing, multiple purpose large-scale sensing can be conducted efficiently. The experimental evaluation with a prototype platform shows the practical feasibility. In addition, the result shows that it is effective to update sensing configuration dynamically.
The proposed method focuses aggregating environmental sensor value from a lot of devices, and, thus, it can treat stream data, such as video or audio or control a specific device directly.
In proposed method, a single-sensing infrastructure can be used by multiple applications, and it admits heterogeneous devices in a single infrastructure. In addition, the proposed method has less technical restriction and developers can implement actual platform with technologies for context.
This research was partially supported by the Japan Ministry of Education, Science, Sports and Culture [Grant-in-Aid for Scientific Research (B) (No.16H02908, No.15H02701 and No.26280115), Young Scientists (B) (No.26730155) and Challenging Exploratory Research (15K12020)].
Inomoto, H., Saiki, S., Nakamura, M. and Matsumoto, S. (2017), "Design and evaluation of mission-oriented sensing platform with military analogy", International Journal of Pervasive Computing and Communications, Vol. 13 No. 1, pp. 76-91. https://doi.org/10.1108/IJPCC-01-2017-0007Download as .RIS
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