Using IoT and smart monitoring devices to optimize the efficiency of large-scale distributed solar farms

Shapsough, Salsabeel; Takrouri, Mohannad; Dhaouadi, Rached; Zualkernan, Imran A.

doi:10.1007/s11276-018-01918-z

Cited by 32 publications

(12 citation statements)

References 44 publications

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“…Also, other research shows that, in Arabian Gulf countries, a smart energy management system using the Internet of Things can reduce costs, especially for air conditioning, which accounts for up to 60% of electricity consumption, while still meeting energy demand [41]. On the other hand, use of the IoT in utilities has a good effect on attainment of efficiency (management of large-scale solar photovoltaic systems) [42] and conservation of resources [43].…”

Section: Utilitiesmentioning

confidence: 99%

An Investigation of the Policies and Crucial Sectors of Smart Cities Based on IoT Application

et al. 2022

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As smart cities (SCs) emerge, the Internet of Things (IoT) is able to simplify more sophisticated and ubiquitous applications employed within these cities. In this regard, we investigate seven predominant sectors including the environment, public transport, utilities, street lighting, waste management, public safety, and smart parking that have a great effect on SC development. Our findings show that for the environment sector, cleaner air and water systems connected to IoT-driven sensors are used to detect the amount of CO2, sulfur oxides, and nitrogen to monitor air quality and to detect water leakage and pH levels. For public transport, IoT systems help traffic management and prevent train delays, for the utilities sector IoT systems are used for reducing overall bills and related costs as well as electricity consumption management. For the street-lighting sector, IoT systems are used for better control of streetlamps and saving energy associated with urban street lighting. For waste management, IoT systems for waste collection and gathering of data regarding the level of waste in the container are effective. In addition, for public safety these systems are important in order to prevent vehicle theft and smartphone loss and to enhance public safety. Finally, IoT systems are effective in reducing congestion in cities and helping drivers to find vacant parking spots using intelligent smart parking.

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Section: Utilitiesmentioning

confidence: 99%

An Investigation of the Policies and Crucial Sectors of Smart Cities Based on IoT Application

et al. 2022

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“…For the purpose of this evaluation, environmental conditions are assumed to be reported per string. The size of packets generated at each level was calculated based on an existing remote solar monitoring system discussed in [54]. Table 4 shows a breakdown of the estimated data mass generated per reporting period.…”

Section: Scalabilitymentioning

confidence: 99%

An IoT-Based Services Infrastructure for Utility-Scale Distributed Solar Farms

Shapsough

Zualkernan

2022

Energies

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Internet of Things (IoT) provides large-scale solutions for efficient resource monitoring and management. As such, the technology has been heavily integrated into domains such as manufacturing, healthcare, agriculture, and utilities, which led to the emergence of sustainable smart cities. The success of smart cities depends on the availability of data, as well as the quality of the data management infrastructure. IoT introduced numerous new software, hardware, and networking technologies designed for efficient and low-cost data transport, storage, and processing. However, proper selection and integration of the correct technologies is crucial to ensuring a positive return on investment for such systems. This paper presents a novel end-to-end infrastructure for solar energy analysis and prediction via edge-based analytics.

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“…Solar energy predictions can be used for effective energy budget planning. Using IoT hardware, software, and communication technologies, Shapsough et al [17] developed a cost-effective system for stakeholders to monitor and efficiently control large-scale solar photovoltaic systems and evaluate the effects of environmental factors on the systems.…”

Section: A Iot For Urban Temperature Monitoringmentioning

confidence: 99%

Using Long Short-Term Memory (LSTM) and Internet of Things (IoT) for Localized Surface Temperature Forecasting in an Urban Environment

Yu¹,

et al. 2021

IEEE Access

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The rising temperature is one of the key indicators of a warming climate, capable of causing extensive stress to biological systems as well as built structures.Ambient temperature collected at ground level can have higher variability than regional weather forecasts, which fail to capture local dynamics. There remains a clear need for accurate air temperature prediction at the suburban scale at high temporal and spatial resolutions. This research proposed a framework based on a long short-term memory (LSTM) deep learning network to generate day-ahead hourly temperature forecasts with high spatial resolution. Air temperature observations are collected at a very fine scale (∼150m) along major roads of New York City (NYC) through the Internet of Things (IoT) data for 2019-2020. The network is a stacked two layer LSTM network, which is able to process the measurements from all sensor locations at the same time and is able to produce predictions for multiple future time steps simultaneously. Experiments showed that the LSTM network outperformed other traditional time series forecasting techniques, such as the persistence model, historical average, AutoRegressive Integrated Moving Average (ARIMA), and feedforward neural networks (FNN). In addition, historical weather observations are collected from in situ weather sensors (i.e., Weather Underground, WU) within the region for the past five years. Experiments were conducted to compare the performance of the LSTM network with different training datasets: 1) IoT data alone, or 2) IoT data with the historical five years of WU data. By leveraging the historical air temperature from WU, the LSTM model achieved a generally increased accuracy by being exposed to more historical patterns that might not be present in the IoT observations. Meanwhile, by using IoT observations, the spatial resolution of air temperature predictions is significantly improved.INDEX TERMS air temperature, Internet of Things (IoT), long short-term memory (LSTM), urban weather

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Using IoT and smart monitoring devices to optimize the efficiency of large-scale distributed solar farms

Cited by 32 publications

References 44 publications

An Investigation of the Policies and Crucial Sectors of Smart Cities Based on IoT Application

An Investigation of the Policies and Crucial Sectors of Smart Cities Based on IoT Application

An IoT-Based Services Infrastructure for Utility-Scale Distributed Solar Farms

Using Long Short-Term Memory (LSTM) and Internet of Things (IoT) for Localized Surface Temperature Forecasting in an Urban Environment

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