1. Monitoring indoor air quality using raspberry pi processor
Authors : Dr.m.v.lakshmaiah, Syed Faiazuddin, Dr.k.tanveer Alam
Pages : 78-81
DOI : http://dx.doi.org/10.21172/1.101.13
Keywords : WSN, Air Pollution, Raspberry Pi2 Processor, GSM-GPRS, Bluetooth, Indoor air quality Indoor environment, Zigbee Gas sensors Smart cities. Abstract :The parameters of the environment to be monitored are chosen as temperature, humidity, volume of CO, volume of CO2, detection of leakage of any gas - smoke, alcohol, LPG. The values of these parameters are transmitted by using Zigbee Pro (S-2) to a base station where they are being monitored. In order to monitor quality of air, a Wireless sensor network (WSN) based new framework is proposed which is based on data acquisition and transmission. The value of temperature and humidity are transmitted over Bluetooth also so that every person in the range of the system can check it over their smart phones and laptops as these parameters hold importance to everyone. CO, a dangerous parameter is monitored with an extra precaution. A text message is sent to the base station through GSM module whenever its volume exceeds a particular safe limit intended for a particular application. Indoor environments are characterized by several pollutant sources. As people typically spend more than 90 % of their time in indoor environments. This work describes the system (iAQ), a low-cost indoor air quality monitoring wireless sensor network system, developed using Raspberry pi Processor, XBee modules and micro sensors, for storage and availability of monitoring data on a web portal in real time. Five micro sensors of environmental parameters (air temperature, humidity, carbon monoxide, carbon dioxide and luminosity) were used. Other sensors can be added for monitoring specific pollutants. The results reveal that the system can provide an effective indoor air quality assessment to prevent exposure risk. In fact, the indoor air quality may be extremely different compared to what is expected for a quality living environment.
Citing this Journal Article :Dr.m.v.lakshmaiah, Syed Faiazuddin, Dr.k.tanveer Alam, "Monitoring indoor air quality using raspberry pi processor", Volume 10 Issue 1 - March 2018, 78-81
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