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Article
Publication date: 3 April 2017

Hikaru Inomoto, Sachio Saiki, Masahide Nakamura and Shinsuke Matsumoto

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Details

International Journal of Pervasive Computing and Communications, vol. 13 no. 1
Type: Research Article
ISSN: 1742-7371

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