Wireless Technology

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability...

This study is sought to address the problem of the 'manual' monitoring system which renders "low" accuracy on monitoring the water value. The existing practice of manual testing uses a refractometer to check the salinity level device and pond thermometers for testing the water temperature of fish farm water environment. It needs extra effort and more workers to regularly monitor such as: opening and closing the gate valve to control the level of fresh and saltwater needed to become accurate 'brackish' water. On the contrary, this research wants to establish an IOT-Based project to attempt solving this existing problem. Hence, this may create a unique system to help monitor and maintain the salinity, temperature and water level using the sensors that triggers the relay switches to automatically open or close the gate valves and operate the motors depending on the parameter's desirable range values that the sensors passed. The sensors and motors also monitor the pond environment between air and water for sufficient increase of oxygen concentration in farm water environment. Likewise, this new IOT-based monitoring system specifically uses Raspberry PI 3B+, Wemos Wireless Microcontroller, Sensors (for water level, conductivity, temperature, toxic gases) and Relay Switches, Equipment (i.e. paddle wheel aerator, water pump and pipe valve), Computer and Mobile Phone, Long Range access point/Point to Point network to cover the entire fish farming areas for wide ranges wireless connectivity, and USB modem which sends SMS messages to keep the management updated with the current water behavior in the farm.