Self-powered weather station for remote areas and difficult-access locations

Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol

The automatic weather system serves to inform farmers, tourists, planners, and others with precise information to help them take the appropriate action. Today, with the advancement of smart technologies, the system has evolved into many sensing methods to gather real-time climate data. This article investigates the modeling and implementation of a low-cost weather station device that also functions to measure air quality. The proposed system based on the Internet of Things (IoT) allows access to real-time climate data for a given area. This system monitors environmental conditions such as ambient temperature, humidity, atmospheric pressure, altitude, and levels of harmful atmospheric gases like CO2 and NO2. This real-time telemetry device uses MQ-135, DHT-11 and BMP280 sensors to gather data. The ESP32 board processes the obtained data from all sensors. Additionally, we present a model for a fuzzy inference system (FIS) that performs parameter categorization using a reasoning procedure and incorporates the results into an air quality index (AQI) that describes the levels of pollution for Al Hoceima city. The FIS takes CO2 and NO2 values as input and returns the AQI. The AQI for Al Hoceima city is categorized into six levels: Excellent, Good, Regular, Bad, Dangerous, and Very Dangerous. Furthermore, the suggested system's block hardware employs the Message Queuing Telemetry Transport (MQTT) protocol to broadcast collected data to a mobile and web application via the Internet. The suggested IoT-embedded device was tested in real life, and the results were promising.

Simultaneous Lightwave and Power Transfer for Internet of Things Devices

A laudable goal toward achieving autonomous internet of things (IoT) devices would be to use the same circuitry for communication and harvesting energy. One way to achieve it is through simultaneous lightwave and power transfer (SLIPT) that consists of using solar cells to harvest energy and receive information signals. Here, a SLIPT-based system that uses a large area solar panel to harvest energy from light sources and decode data signals is designed. The designed system is equipped with an infrared sensor used to detect the movements of an unmanned aerial vehicle. We equally discuss the wide-scale deployment of IoT devices with SLIPT capability.