A novel air quality monitoring and improvement system based on wireless sensor and actuator networks using LoRa communication

A low-cost wireless extension for object detection and data logging for educational robotics using the ESP-NOW protocol

In recent years, inexpensive and easy to use robotics platforms have been incorporated into middle school, high school, and college educational curricula and competitions all over the world. Students have access to advanced microprocessors and sensor systems that engage, educate, and encourage their creativity. In this study, the capabilities of the widely available VEX Robotics System are extended using the wireless ESP-NOW protocol to allow for real-time data logging and to extend the computational capabilities of the system. Specifically, this study presents an open source system that interfaces a VEX V5 microprocessor, an OpenMV camera, and a computer. Images from OpenMV are sent to a computer where object detection algorithms can be run and instructions sent to the VEX V5 microprocessor while system data and sensor readings are sent from the VEX V5 microprocessor to the computer. System performance was evaluated as a function of distance between transmitter and receiver, data packet round trip timing, and object detection using YoloV8. Three sample applications are detailed including the evaluation of a vision-based object sorting machine, a drivetrain trajectory analysis, and a proportional-integral-derivative (PID) control algorithm tuning experiment. It was concluded that the system is well suited for real time object detection tasks and could play an important role in improving robotics education.

Bee colony remote monitoring based on IoT using ESP-NOW protocol

Information and communication technologies, specifically the Internet of Things (IoT), have been widely used in many agricultural practices, including beekeeping, where the adoption of advanced technologies has an increasing trend. Implementation of precision apiculture methods into beekeeping practice depends on availability and cost-effectiveness of honey bee colony monitoring systems. This study presents a developed bee colony monitoring system based on the IoT concept and using ESP8266 and ESP32 microchips. The monitoring system uses the ESP-NOW protocol for data exchange within the apiary and a GSM (Global System for Mobile communication)/GPRS (General packet radio service) external interface for packet-based communication with a remote server on the Internet. The local sensor network was constructed in a star type logical topology with one central node. The use of ESP-NOW protocol as a communication technology added an advantage of longer communication distance between measurement nodes in comparison to a previously used Wi-Fi based approach and faster data exchange. Within the study, five monitoring devices were used for real-time bee colony monitoring in Latvia. The bee colony monitoring took place from 01.06.2022 till 31.08.2022. Within this study, the distance between ESP-NOW enabled devices and power consumption of the monitoring and main nodes were evaluated as well. As a result, it was concluded that the ESP-NOW protocol is well suited for the IoT solution development for honeybee colony monitoring. It reduces the time needed to transmit data between nodes (over a large enough distance), therefore ensuring that the measurement nodes operate in an even lower power consumption mode.

A Communication Framework for Image Transmission through LPWAN Technology

Analyzing the conditions of use and selecting which technology is more efficient to apply is required when transmitting information through wireless networks.The Internet of Things (IoT) has gained traction in industry and academia as a paradigm in which information and communication technologies merge to deliver unique solutions by detecting, actuating, calculating, and sharing massive volumes of data via embedded systems. In this scenario, Low-Power Wide-Area Networks (LPWAN) appear to be an attractive solution for node connectivity. Typical IoT solutions demand flexible restrictions for wireless communication networks in terms of data rates and latency in exchange for having larger communication ranges and low energy consumption. Nonetheless, as the amount of data and data speeds demanded for particular applications increase, such as image transmissions, IoT network connectivity deteriorates. This paper proposes a communication architecture for image transmission across LPWAN networks utilizing LoRa modulation. The framework combines image processing techniques (classification, compressive sensing (CS), and reconstruction) with an investigation of LoRa modulation parameters using a Software-Defined Radio (SDR) environment. The results show that is possible to communicate an image of 128×128 pixels with four packets and one frequency channel in 2.51 s.