A system for efficient dissemination of weather forecasts for sustainable solar-powered sensors

Renner, Christian; Nguyen, Phu Anh Tuan

doi:10.1109/sustainit.2015.7101371

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…Continuous investigations are conducted to improve the prediction performance. Renner in [19] presented a new architecture that automatically obtains global weather forecasts from freely available online resources and disseminates them into the sensor network. Another solar energy prediction scheme is proposed by Kosunalp using Q-learning to improve the estimation [13].…”

Section: Related Workmentioning

confidence: 99%

UD-WCMA: An energy estimation and forecast scheme for solar powered wireless sensor networks

Dehwah

Elmetennani

Claudel

2017

Journal of Network and Computer Applications

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Energy estimation and forecast represents an important role for energy management in solar-powered wireless sensor networks (WSNs). In general, the energy in such networks is managed over a finite time horizon in the future based on input solar power forecasts to enable continuous operation of the WSNs and achieve the sensing objectives while ensuring that no node runs out of energy. In this article, we propose a dynamic version of the weather conditioned moving average technique (UD-WCMA) to estimate and predict the variations of the solar power in a wireless sensor network. The presented approach combines the information from the real-time measurement data and a set of stored profiles representing the energy patterns in the WSNs location to update the prediction model. The UD-WCMA scheme is based on adaptive weighting parameters depending on the weather changes which makes it flexible compared to the existing estimation schemes without any precalibration. A performance analysis has been performed considering real irradiance profiles to assess the UD-WCMA prediction accuracy. Comparative numerical tests to standard forecasting schemes (EWMA, WCMA, and Pro-Energy) shows the outperformance of the new algorithm. The experimental validation has proven the interesting features of the UD-WCMA in real time low power sensor nodes.

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Section: Related Workmentioning

confidence: 99%

UD-WCMA: An energy estimation and forecast scheme for solar powered wireless sensor networks

Dehwah

Elmetennani

Claudel

2017

Journal of Network and Computer Applications

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“…A major field of current research consists in developing intelligent systems capable of integrating environmental data, to improve efficiency in the use of resources and to enable sustainable functioning of man-made utilities. This can be achieved by making an intelligent use of environmental variables forecasts [ 3 ], for applications such as photovoltaic plants and micro-grids [ 4 , 5 , 6 ], where global radiation and air temperature forecasts play an important role, in agricultural applications [ 7 , 8 ] for greenhouse environmental control and irrigation management, in energy management in buildings [ 9 , 10 ], where predictions of solar radiation, air temperature and relative humidity offer the possibility of important energy savings, as well as in sensor networks, with nodes powered by miniature solar harvesters, where forecasts of solar radiation reduces the risk of temporary depletion and increases their utility [ 11 ]. These selected works, which are a small subset of a much larger body of research, undoubtedly illustrate the need of a weather station that, besides measurement of atmospheric variables, provides their forecasts autonomously, and makes them available wirelessly to the application at hand.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Weather Station

Mestre

Ruano

Duarte

et al. 2015

Sensors

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Accurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead.

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“…To address this issue, different sensor node deployment optimization [4,5] and data collection protocols [6] have been proposed. Some of the protocols are application specific [7][8][9][10][11], while others are for general application [12]. Routing protocols based on the clustering are considered an energy-efficient technique in terms of data aggregation and sending to the BS [13].…”

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confidence: 99%

A QoS-Aware Data Collection Protocol for LLNs in Fog-Enabled Internet of Things

Hosen

Singh

Sharma

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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Improving quality of service (QoS) of low power and lossy networks (LLNs) in internet of things (IoT) is a major challenge. Cluster-based routing technique is an effective approach to achieve this goal. This paper proposes a QoS-aware clustering-based routing (QACR) mechanism for LLNs in Fogenabled IoT which provides a clustering, a cluster head (CH) election, and a routing path selection technique. The clustering adopts the community detection algorithm that partitions the network into clusters with available nodes' connectivity. The CH election and relay node selection both are weighted by the rank of the nodes which take node's energy, received signal strength, link quality, and number of cluster members into consideration as the ranking metrics. The number of CHs in a cluster is adaptive and varied according to a cluster state to balance the energy consumption of nodes. Besides, the protocol uses the CH role handover technique during CH election that decreases the control messages for the periodic election and cluster formation in detail. An evaluation of the QACR has performed through simulations for various scenarios. The obtained results show that the QACR improves the QoS in terms of packet delivery ratio, latency, and network lifetime compared to the existing protocols.

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A system for efficient dissemination of weather forecasts for sustainable solar-powered sensors

Cited by 5 publications

References 25 publications

UD-WCMA: An energy estimation and forecast scheme for solar powered wireless sensor networks

UD-WCMA: An energy estimation and forecast scheme for solar powered wireless sensor networks

An Intelligent Weather Station

A QoS-Aware Data Collection Protocol for LLNs in Fog-Enabled Internet of Things

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