IoT Cloud-Based Power Quality Extended Functionality for Grid-Interactive Appliance Controllers

Garrido-Zafra, Joaquín; Gil-de-Castro, Aurora; Fernandez, Rafael Savariego; Reyes, Matias Linan; García, Félix C.; Moreno-Munoz, A.

doi:10.1109/tia.2022.3160410

Cited by 11 publications

(2 citation statements)

References 26 publications

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“…Incorporating awake and sleeping techniques into smart livestock husbandry techniques would be beneficial for future research [114,115]. Researchers could apply techniques like sensor-and actuator-based energy utilization methodologies [116,117], cloud-based energy optimization [118,119], and network-level energy optimization [120][121][122] for energy consumption.…”

Section: Energy Consumptionmentioning

confidence: 99%

Systematic Review on Internet of Things in Smart Livestock Management Systems

Terence,

Immaculate,

Raj

et al. 2024

Sustainability

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The advent of the Internet of Things (IoT) has sparked the creation of numerous improved and new applications across numerous industries. Data collection from remote locations and remote object control are made possible by Internet of Things technology. The IoT has numerous applications in fields such as education, healthcare, agriculture, smart cities, and smart homes. Numerous studies have recently employed IoT technology to automate livestock farm operations. We looked at IoT-based livestock farm management systems in this study. To select the publications for this investigation, we conducted a systematic literature review (SLR) that complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. The selected articles were divided into different categories according to their applications. Sensors, actuators, the main controller (gateway), communication protocols, storage, energy consumption, the use of renewable energy sources, scalability, security, and prediction techniques applied to the data collected for future prediction were all examined in this study as IoT technologies used to monitor animals. In this study, we found that only 22% of the articles addressed security concerns, 24% discussed scalability, 16% discussed renewable energy, 18% attempted energy consumption, and 33% employed prediction techniques based on the collected data. The challenges and future directions of intelligent livestock farming are emphasized.

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Section: Energy Consumptionmentioning

confidence: 99%

Systematic Review on Internet of Things in Smart Livestock Management Systems

Terence,

Immaculate,

Raj

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Therefore, the disaggregated and continuous measurement of certain PQ indicators employing the IoT platform developed, as depicted in Fig. 3, can contribute to a more accurate assessment of resources in the MG [12].…”

Section: Position and Work In Progressmentioning

confidence: 99%