Performance Evaluation of Solar PV Inverter Controls for Overvoltage Mitigation in MV Distribution Networks

By integrating physical objects and facilitating data-driven decision-making, the Internet of Things (IoT) is transforming several sectors. Through the provision of individualised treatment plans, real-time health data analysis, and remote patient monitoring, it is vital to the modernization of healthcare systems. IoT technologies are essential to the development of smart cities, resource allocation optimisation, public safety improvement, and traffic congestion reduction. IoT-driven smart farming automates machinery, optimises irrigation, and monitors crop conditions. As IoT makes it possible to create smart grids, save energy waste, and increase grid dependability, the energy landscape is changing. IoT makes it easier to apply Industry 4.0 ideas in the manufacturing sector, converting conventional factories into networked, intelligent systems. Reducing operating costs and increasing productivity are the outcomes of implementing IoT-enabled sensors, robots, and data analytics to improve supply chain management, predictive maintenance, and production efficiency. Innovation, sustainability, and efficiency are becoming more and more possible as a result of the Internet of Things' integration across many industries. This review also showcases the relevant prospects of IoT applications in the fields mentioned.

Section: Smart Grid and Energy Savingmentioning

confidence: 99%

Transformative Applications of IoT in Diverse Industries: A Mini Review

Krishna Sannasy Rao,

Chong Peng Lean,

Kong Feng Yuan

et al. 2024

“…To extend battery life, energy-efficient design concepts like duty cycling and sleep modes are also used. Furthermore, developments in energy harvesting technologies help power IoT sensors without requiring regular battery changes or cable connections to the grid for electricity [23][24][25][26].…”

Section: Figmentioning

confidence: 99%

A Raspberry Pi-Powered IoT Smart Farming System for Efficient Water Irrigation and Crop Monitoring

Chong Peng Lean,

Gophinath Krishnan,

Chen Li

et al. 2024

Self Cite

Water irrigation remain as a challenge to supply adequate amount of water to sustain the growth of plant and crops yield along the year in certain part of the world which are heavily affected by climate change. This scenario creates a huge risk toward the world food supply chain. Hence, the application of smart farming system is crucially important now to pave the way for a better the agriculture monitoring system to replace traditional manual monitoring labour by farmers. The smart farming system are usually equipped with environmental stimuli sensing system such as temperature, humidity, soil moisture, light intensity sensing sensors coupled with automation actuators to control the water irrigation rate for the crops in order to save water and at the same time provide adequate water supply for plant growth. The aim of using such smart farming system is to enable higher crops production and less human labour at the same time optimising resources available to minimize cost of farming. Hence, this paper aims to introduce a novel approach of a Raspberry Pi powered IoT smart farming system (ISFS) which can incorporate autonomous monitoring of plant irrigation, temperature, humidity, soil moisture and light intensity, to design a smartphone app that allows users to monitor plantation-related conditions in a user-friendly manner, and to enable automatic control of a drip irrigation system for plants based on data obtained on soil moisture, temperature and sunlight intensity. The proposed prototype with the functionality mentioned is aim to resolve the existing problem and to meet the demand of smart farming application in current era.

“…Furthermore, ensuring the reliability and accuracy of AI and ML algorithms in smart home applications is essential. ML models must be trained on diverse and representative datasets to ensure robust performance across different environments and user scenarios [37][38][39][40]. Additionally, addressing algorithmic bias and ensuring fairness and transparency in decision-making processes are critical considerations.…”

Section: Smart Home Facilitymentioning

confidence: 99%

AI and ML in IR4.0: A Short Review of Applications and Challenges

Sannasy Rao,

Chong Peng Lean,

et al. 2024

Self Cite

Artificial intelligence and machine learning are essential for the development of IR4.0 due to their ability to analyse vast amounts of data, automate processes, and drive innovation across various sectors. These technologies enable intelligent decision-making, predictive analytics, and automation, leading to increased efficiency, productivity, and competitiveness in the digital age. In IR4.0, AI and ML power smart systems and connected devices, transforming industries. They facilitate the integration of digital, physical, and biological systems, enabling the creation of personalized medicine and medical diagnosis smart manufacturing, self-autonomous driving vehicles, smart cities, and smart home. Hence, this review aims to address the contribution of AI and ML in the development of medical diagnosis, smart manufacturing, smart cars, smart cities, and smart homes as well as to highlight the existing challenges faced by AI and ML in these fields. This review also showcases the relevant prospects of AI and ML applications in the fields mentioned.