Micro energy harvesting for IoT platform: Review analysis toward future research opportunities

Sarker, Mahidur R.; Riaz, Amna; Lipu, M.S. Hossain; Md Saad, Mohamad Hanif; Ahmad, Mohammad Nazir; Kadir, Rabiah Abdul; Olazagoitia, José Luis

doi:10.1016/j.heliyon.2024.e27778

Cited by 2 publications

(1 citation statement)

References 165 publications

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“…This will help to minimize electricity costs while also benefiting the environment [123,124]. Also, future IoT-based animal monitoring systems could concentrate more on micro-energy harvesting techniques [125], multi-model energy harvesting schemes [126], and microgrid structures [127] for renewable energy generation and distribution.…”

Section: Usage Of Renewable Energymentioning

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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