An IoT framework for smart power management system

Dey, Shopan; Kar, Tapasundar; Iqbal, Asif; Roychoudhury, Doipayan; Laha, Subham; Chowdhury, Anubhab; Chakraborty, Anirban; Shaw, Kaunteya; Nayak, Somen; Basu, Shatabdi; Guhathakurta, Rajib; Dey, Ratul

doi:10.1109/iemcon.2017.8117195

Cited by 3 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, applying an energy-saving mechanism to prolong the uptime. To save energy, several power-saving techniques have been used in the literature, such as duty cycling, transmitted data reduction, transceiver optimization, energy-provision schemes, overhead protocol reduction, voltage control, and current control [16][17][18][19][20][21][22][23] WSNs employ many cutting-edge energy management strategies. By creating symmetric clusters, Barzegari and Mossadry devised a c-means clustering technique [24].…”

Section: Related Workmentioning

confidence: 99%

Quad-band GSM/GPRS Enabled Low-Power Sensor Node Design For Outdoor IoT Applications

Maduranga¹

2022

Preprint

View full text Add to dashboard Cite

<p>People have become increasingly aware of the environment in which they live in recent years. This awareness has prompted the development of a reliable environmental monitoring system. This paper presents an energy-efficient and low-power sensor node that could be used for outdoor Internet of Things (IoT) applications to monitor real-time environment conditions such as humidity and temperature remotely. The proposed sensor node could directly connect with a cellular base station over GSM/GPRS quad-bands 850MHz,900MHz,1800MHz, and 1900MHz without needing any Access Point(AP) in the network. The sensor node consists of a central controller based on Atmega328, a communication module on SIM800, DHT22 temperature, and a humidity sensor with a solar-powered charging system. The system is specially designed for robust IoT outdoor applications such as environment monitoring in wilds, large-scale farms, forests, etc. For optimal usage of the power of the battery, an energy-saving mechanism is proposed based on deep sleep scheduling, thus considerably reducing the power consumption and prolonging the up-time of the sensor node. </p>

show abstract