Over the past few years, there has been an increasing fascination with electric unmanned aerial vehicles (UAVs) because of their capacity to undertake demanding and perilous missions while also delivering advantages in terms of flexibility, safety, and expenses. These UAVs are revolutionizing various public services, encompassing real-time surveillance, search and rescue operations, wildlife assessments, delivery services, wireless connectivity, and precise farming. To enhance their efficiency and duration, UAVs typically employ a hybrid power system. This system integrates diverse energy sources, such as fuel cells, batteries, solar cells, and supercapacitors. The selection of an appropriate hybrid power arrangement and the implementation of an effective energy management system are crucial for the successful functioning of advanced UAVs. This article specifically concentrates on UAV platforms powered by batteries, incorporating innovative technologies, like in-flight recharging via laser beams and tethering. It provides an all-encompassing and evaluative examination of the current cutting-edge power supply configurations, with the objective of identifying deficiencies, presenting perspectives, and offering recommendations for future consideration in this domain.

Unmanned aerial vehicle (UAV) usage is increasing drastically worldwide as UAVs are used in various industries for many applications, such as inspection, logistics, agriculture, and many more. This is because performing a task using UAV makes the job more efficient and reduces the workload needed. However, for a UAV to be operated manually or autonomously, the UAV must be equipped with proper safety features. An anti-collision system is one of the most crucial and fundamental safety features that UAVs must be equipped with. The anti-collision system allows the UAV to maintain a safe distance from any obstacles. The anti-collision technologies are of crucial relevance to assure the survival and safety of UAVs. Anti-collision of UAVs can be varied in the aspect of sensor usage and the system’s working principle. This article provides a comprehensive overview of anti-collision technologies for UAVs. It also presents drone safety laws and regulations that prevent a collision at the policy level. The process of anti-collision technologies is studied from three aspects: Obstacle detection, collision prediction, and collision avoidance. A detailed overview and comparison of the methods of each element and an analysis of their advantages and disadvantages have been provided. In addition, the future trends of UAV anti-collision technologies from the viewpoint of fast obstacle detection and wireless networking are presented.

The growing reliance on Unmanned Aerial Vehicles (UAVs) necessitates efficient energy management to ensure optimal performance and longevity. This study investigates the energy consumption patterns and efficiency degradation in DJI Mini 2 drone batteries by the utilization of a deep neural...

Over the past few years, there has been an increasing fascination with electric unmanned aerial vehicles (UAVs) because of their capacity to undertake demanding and perilous missions, while also delivering advantages in terms of flexibility, safety, and expenses. These UAVs are revolutionizing various public services, encompassing real-time surveillance, search and rescue operations, wildlife assessments, delivery services, wireless connectivity, and precise farming. To enhance their efficiency and duration, UAVs typically employ a hybrid power system. This system integrates diverse energy sources, such as fuel cells, batteries, solar cells, and supercapacitors. The selection of an appropriate hybrid power arrangement and the implementation of an effective energy management system are crucial for the successful functioning of advanced UAVs. This article specifically concentrates on UAV platforms powered by batteries, incorporating innovative technologies like in-flight recharging via laser beams and tethering. It provides an all-encompassing and evaluative examination of the current cutting-edge power supply configurations, with the objective of identifying deficiencies, presenting perspectives, and offering recommendations for future consideration in this domain.

In the paper, the hardware and software of the IoT weather monitoring system have been developed. The hardware of the IoT weather monitoring system consists of the microcontroller device which is developed on the Arduino Mega2560 board, digital pressure, temperature and humidity sensor BME280, Wi-Fi module ESP-01 built on the ESP8266 chip and the 16×2 alphanumeric LCD based on the Hitachi HD44780 controller. The electronic circuit and the model of the microcontroller weather monitoring device have been created in Proteus VSM. The operation algorithm of the IoT weather monitoring system has been developed. The IoT device monitors such weather parameters as: atmospheric pressure, temperature and relative humidity. The software modules for communication with the BME280 sensor and Wi-Fi module ESP-01 and main data collection and acquisition software for the ATmega2560 microcontroller of the Arduino Mega2560 board have been created. The software for communication with the ThingsBoard IoT platform and Mosquitto MQTT broker has been created. The dashboards for weather data visualization on the IoT platform ThingsBoard using ThingsBoard Dashboard and from the Mosquitto MQTT broker using Node-RED have been created. The operation of the microcontroller weather monitoring device has been simulated in Proteus ISIS. The prototype of the microcontroller weather monitoring device has been built on a solderless breadboard and the operation of the IoT weather monitoring system has been tested.

In the paper, the spectrum analyzer of vibration accelerations using the Raspberry Pi microcomputer and 3-axis digital MEMS ADXL345 accelerometer has been developed. The system includes accelerometer driver for Raspberry Pi, software for data acquiring and processing from the acceleration sensor, conversion of the vibration acceleration signals from time domain into frequency domain using DFT, graph plotting of the vibration accelerations and their spectra.