The Internet of Medical Things (IoMT) is the subset of the Internet of Things (IoT) that connects multiple medical devices, collect information/data from devices, and transmits and process data in real-time. IoMT is crucial for increasing electronic device accuracy, reliability, and productivity in the healthcare industry. IoMT has emerged as a next-generation bio-analytical tool that converges network-linked biomedical devices with relevant software applications for advancing human health. Adapting IoMT and associated technologies has fixed several problems using telemedicine, remote monitoring, sensors, robotics, etc. However, adopting IoMT technologies for a large population is challenging due to extensive data management, privacy, security, upgradation, scalability, etc. Although significant research has been carried out in this domain, identifying emerging trends and highlighting the technological advancement and challenges within IoMT is required for its success. Moreover, it will aid policymakers, scientists, healthcare practitioners, and researchers to measure the pertinence of IoMT in healthcare sectors more efficiently. This review discusses the evolution of IoMT, Machine Learning Integration, Security, and interoperability challenges of IoMT devices.

Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones’ ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.

Automation has led to the growth of industries in recent years. For better performance of industrial process automated machines are used. Image processing has led to advancements in applications of robotics and embedded systems. Sorting of objects are usually done by humans which takes a lot of time and effort. Using Computer Vision techniques, a conveyor belt system is developed using stepper, servo motors and mechanical structures, which can identify and sort various objects. This reduces human effort, time consumed, and also improves the time to market the products.

Indoor navigation is favorable for every person, and is exclusively essential for the visually challenged. The proposed method uses Light-Fidelity (Li-Fi) technology for transmission of the information. Li-Fi is apt for high-density wireless data exposure in restrained regions that are free of hindrances. Li-Fi is a progressing branch of Optical Wireless Communication and can give greater data rate transmission laterally with the proficiency to employ surplus users since it uses a spectrum bandwidth of wider-range.