Assessment on economic power management for smart city through IoT sensor model

Khan, Bhola; Kirubadevi, S; Agarwal, Swathi; Prasad, M; Bhaskar, Thupakula; Ambethkar, M. Raja

doi:10.1016/j.measen.2022.100515

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…The infrastructure supporting the energy market has undergone tremendous development. The IoT sensors currently incorporate the processing power of every energy provider, which could increase their energy consumption [ 9 ]. The MEH system should be created to enable the connectivity of IoT platform with a self-powered function to solve the energy crisis [ 10 ].…”

Section: State Of Artmentioning

confidence: 99%

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

Sarker,

Riaz,

Lipu

et al. 2024

Heliyon

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Section: State Of Artmentioning

confidence: 99%

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

Sarker,

Riaz,

Lipu

et al. 2024

Heliyon

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“…Smart health applications include the use of IoT with sensors to monitor health conditions and provide early warnings if health problems occur [26]. Smart city applications include the use of IoT technology to increase efficiency and productivity in various aspects of city life, such as transportation, waste management, and security [27], [28]. In its application, IoT has many benefits, such as making it easier to operate devices remotely, increasing efficiency and productivity, and providing solutions to various problems in everyday life.…”

Section: Internet Of Things (Iot)mentioning

confidence: 99%

Impact of Training Kit-Based Internet of Things to Learn Microcontroller Viewed in Cognitive Domain

Wildan Habibi,

Asto Buditjahjanto

2024

TEM Journal

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This research aims to find out how effective the IoT microcontroller training kit learning media is and to analyze the effect of using the IoT microcontroller training kit compared to the common microcontroller training kit on students' cognitive learning outcomes in learning microcontroller and microprocessor programming techniques. The normalized gain method was used to determine the effectiveness of the IoT microcontroller training kit learning media. The ANOVA method was used to determine the effect of using the IoT microcontroller training kit and common microcontroller training kit on the average student cognitive learning outcomes. The research results show that the IoT microcontroller training kit learning media has a normalized gain value of 59.62% in the effective enough category. The average cognitive learning outcomes of students using the IoT microcontroller training kit are greater than those using the regular microcontroller training kit, according to the results of the study using one-way ANOVA, where the p-value is less than the α value of 0.05. This IoT microcontroller training kit can be used to improve students' cognition regarding microcontroller learning in vocational schools.

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Assessment on economic power management for smart city through IoT sensor model

Cited by 2 publications

References 13 publications

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

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

Impact of Training Kit-Based Internet of Things to Learn Microcontroller Viewed in Cognitive Domain

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