Attention Makers



MAKERS: Usman Maqsood

Environmental conditions always have an adverse effect on the comfort of life. It damages materials and causes health problems. There is a need to maintain it and control it on some basic or higher level. Since wireless technology is the key to connectivity these days, a lot of research is being done to make a more effective, low powered and efficient system that can measure respective environmental elements.Our project is based on a body area network architecture. It consists of wireless distributed monitoring and control nodes to monitor the happenings in the environment and also control it. Our project monitors both the indoor and outdoor environment. The environmental elements we are monitoring include temperature, humidity, air quality, ambient light, atmospheric pressure, soil moisture and occupancy. The control includes turning a light bulb, heater and a fan On/Off. The communication of the entire system is based on an RF network using NRF24L01+ and is directly linked to a web server through which the entire RF network can be accessed. We have used all off the shelf sensor modules for better accuracy and have interfaced them with Arduino. Along with this we have also developed our own web page to show live data from the nodes. An additional feature our project includes is the "prediction of the environment" in near time by "extrapolating" a set of values taken from the environment. A database is also maintain so the data or the readings of various environmental conditions can be looked at and analysed. This data can also be downloaded. The server/website can be accessed from any device like smartphones, computers, and tablets. This system can be used to reduce the number of seasonal colds and flues. This network for environmental monitoring and controlling has a number of applications. The most important being in high rise buildings like offices, apartments and hotels. Hospitals are another target for implementing this system so a comfortable environment is provided to the patients. It is imperative that the sensitivity of environmental conditions be kept in mind for the chemical, material, pharmaceutical and textile industries along with the laboratory where experimentations take place. For the future we are going to make the network artificially intelligent to learn from the environment and adjust the environment itself.

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