Omar Munoz

Autonomous navigation vehicles are increasingly used in aerospace, marine, and subterranean operations, including aerial inspection, underwater exploration, search-and-rescue missions, and infrastructure monitoring in GNSS-denied environments. Exteroceptive sensors are used in these systems by enabling mapping, localization, obstacle detection, path planning, and real-time decision-making. The exteroceptive sensors include LiDAR, sonar, monocular cameras, stereo cameras, RGB-D cameras, laser scanners, ultrasonic sensors, and radar. However, for autonomous navigation vehicle tasks, LiDAR, sonar, radar, RGB-D, stereo, and monocular cameras are suitable due to their accuracy, reliability, and ability to provide detailed environmental perception. Recent advancements have facilitated the development of diverse principles and architectures designed to enhance accuracy, scanning efficiency, and compactness. Each of these variants has specific advantages and limitations, which must be carefully considered in the development of applications in autonomous navigation vehicles. This review presents an overview of exteroceptive sensors for ground, underwater, and aerial autonomous vehicles, highlighting operating principles, architectures, and recent technological advances. This review analyzes advantages, limitations, and applications to provide a valuable reference for students, engineers, and researchers aiming to design efficient, adaptive, and accurate autonomous navigation systems across diverse environments.

Electricity consumption is rising due to population growth, climate change, urbanization, and the increasing use of electronic devices. The trend of the Internet of Things has contributed to the creation of devices that promote the thrift and efficient use of electrical energy. Currently, most projects relating to this issue focus solely on monitoring energy consumption without providing relevant parameters or switching on/off electronic devices. Therefore, this paper presents in detail the design, construction, and validation of a smart meter with load control aimed at being part of a home energy management system. With its own electronic design, the proposal differs from others in many aspects. For example, it was developed using a simple IoT architecture with in-built WiFi technology to enable direct connection to the internet, while at the same time being big enough to be part of standardized electrical enclosures. Unlike other smart meters with load control, this one not only provides the amount of energy consumption, but rms current and voltage, active, reactive, and apparent power, reactive energy, and power factor—parameters that could be useful for future studies. In addition, this work presents evidence based on experimentation that the prototype in all its readings achieves an absolute percentage error of less than 1%. A real-life application of the device was also demonstrated in this document by measuring different appliances and switching them on/off manually and automatically using a web-deployed application.