The digital revolution led by the Internet of Things (IoT) is already reshaping several traditional business sectors. Moreover, because of its very nature, the promise of the IoT is also to reduce energy consumption and pollutant emissions in several environmental scenarios. At the same time, it is desirable to keep the development of IoT as sustainable as possible, hence truly realizing the vision of the green IoT. In this paper, we show how a full-stack IoT framework can alleviate some real environmental problems afflicting countries in Western Africa. We present three real IoT-based deployments currently hosted in two rural areas of Senegal and Ghana and one metropolitan area of Togo. These testbeds are connected to a Cloud-based software platform, purposely designed and engineered to address some very specific environmental, economic, and social requirements of the region.
As an important issue reflecting the QoS of the sensing task, coverage problem impacts widely on the performance of wireless sensor networks. The target coverage lifetime maximization problem is yet a challenging problem, which tries to settle a compromise between managing the coverage of a set of targets and maximizing the lifetime of the network. This problem becomes more accurate when targets detection is distance dependent. In this paper, we address the target coverage lifetime maximization problem by considering a probabilistic coverage model, which takes into account the distance parameter. We propose an algorithm based on a modified version of the classical well-known weighed set cover which organizes sensors in disjoint and non-disjoint set covers. Performance evaluation of our solution indicated good performance in managing coverage of targets while extending the network lifetime.
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