Abstract
The driving force behind the smart city initiative is to offer better, more specialized services which can improve the quality of life of the citizens while promoting sustainability. To achieve both of these apparently competing goals, services must be increasingly autonomous and continuously adaptive to changes in their environment and the information coming from other services. In this paper we focus on smart lighting, a relevant application domain for which we propose an intelligent street light control system based on adaptive behavior rules. We evaluate our approach by using a simulator which combines wireless sensor networks and belief-desire-intention (BDI) agents to enable a precise simulation of both the city infrastructure and the adaptive behavior that it implements. The results reveal energy savings of close to 35% when the lighting system implements an adaptive behavior as opposed to a rigid, predefined behavior.
Highlights
Providing an appropriate level of city lighting in public spaces is an important issue both for citizens and city councils
This paper contributes to the state-of-the-art in two ways: (1) it describes a way of modeling and simulating the features of smart cities scenarios such that we can estimate the potential energy savings before deployment, and (2) it proposes an adaptive control system that can be implemented by the devices that compose the smart city infrastructure and which ensures sustainability without sacrificing the level of services offered to the citizens
This paper presents an intelligent street light control system that enables multiphase light sources to adapt their intensity to the environment conditions
Summary
Providing an appropriate level of city lighting in public spaces is an important issue both for citizens and city councils. The drawback when evaluating the impact of such approaches is that the estimation of the energy savings entailed by this kind of lighting systems is not as straightforward as calculating the benefit of lamppost replacement This is due to the potential complexity of the control system and the circumstances that may affect its behavior. In this paper we introduce a simulator for intelligent street light control systems This simulator allows users to evaluate the energy efficiency of different public lighting configurations before deciding on a solution and implementing it on International Journal of Distributed Sensor Networks site. The application could define a rule to reduce the intensity of a street light if additional nearby lighting is detected This continuous adaptation to the actual conditions provides flexibility to the applications running on the devices and results in a sustainable usage of the smart city infrastructure.
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