Diesel electrical generators are essential for providing reliable backup power during grid outages, ensuring the continuous operation of critical services such as hospitals, industries, and communication systems. These generators require instantaneous monitoring and control to optimize their performance and longevity. The Internet of Things facilitates efficient monitoring and enables remote control with a faster response time than human intervention, thereby helping to prevent potential damage or system failures. This research introduced the Internet of Things technology and its general architecture. The study first presented an abstract framework of IoT-based monitoring and controlling technology, divided into three layers: perception, network, and application. It then discussed the terminology related to electrical generators, the parameters monitored, and their operational environments. In addition, the advantages and challenges associated with integrating it with electrical generators were discussed. Finally, the research reviewed and analyzed several practical applications and case studies integrating IoT with diesel electrical generators, highlighting key challenges and proposing solutions. This work provided theoretical and practical insights into IoT-based monitoring and control systems for electrical generators.
Advanced prosthetics are a crucial aspect of rehabilitation technology and are receiving increased attention globally. Approximately 2 million people require prosthetic limbs, presenting opportunities for enhancing their quality of life. State-of-the-art technologies such as realistic arms and myoelectric prostheses are gaining popularity. Progress in sensor technology, artificial intelligence, and materials has driven the field forward. Various types of controllers, including direct, pattern recognition, and proportional-derivative, have been developed. Integration of material science, computer science, artificial intelligence, and neurology has facilitated controller advancements. Techniques like targeted muscle reinnervation and Osseo integrated prostheses offer improved surgical options. Gesture recognition technologies and intelligent sensors are enhancing hand control. Future advancements will involve machine learning, artificial intelligence, and sensing techniques, while ethical concerns must be addressed. Advanced myoelectric prostheses, also known as myocontrolled or lower-limb micromod investigative prostheses, have a patient acceptance rate of 75% to 80%. However, while these methods offer advantages, there are also drawbacks. Integrating different types of controllers for these smart prostheses and enhancing the overall device's strength and robustness will have a significant impact. This discussion focuses on various types of smart prosthetic controllers, dividing muscle activity into extracellular myoelectric potential and EEG signals