Air Quality Monitoring System Based on IoT using Raspberry Pi

被引:0
作者
Kumar, Somansh [1 ]
Jasuja, Ashish [1 ]
机构
[1] NIT Kurukshetra, Sch VLSI Design & Embedded Syst, Kurukshetra, Haryana, India
来源
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA) | 2017年
关键词
Air Quality Monitoring; Internet of Things; Arduino Uno; Raspberry pi; cloud computing;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Air pollution is the largest environmental and public health challenge in the world today. Air pollution leads to adverse effects on Human health, climate and ecosystem. Air is getting polluted because of release of Toxic gases by industries, vehicular emissions and increased concentration of harmful gases and particulate matter in the atmosphere. Particulate matter is one of the most important parameter having the significant contribution to the increase in air pollution. This creates a need for measurement and analysis of real-time air quality monitoring so that appropriate decisions can be taken in a timely period. This paper presents a real-time standalone air quality monitoring system which includes various parameters: PM 2.5, carbon monoxide, carbon dioxide, temperature, humidity and air pressure. Internet of Things is nowadays finding profound use in each and every sector, plays a key role in our air quality monitoring system too. Internet of Things converging with cloud computing offers a novel technique for better management of data coming from different sensors, collected and transmitted by low power, low cost ARM based minicomputer Raspberry pi. The system is tested in Delhi and the measurements are compared with the data provided by the local environment control authority and are presented in a tabular form. The values of the parameters measured are shown in IBM Bluemix Cloud.
引用
收藏
页码:1341 / 1346
页数:6
相关论文
共 15 条
[1]  
[Anonymous], RASPBERRY PI INTERNE
[2]  
Baralis E, 2016, 2016 39TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), P1464, DOI 10.1109/MIPRO.2016.7522370
[3]   Energy-Efficient Cloud Computing [J].
Berl, Andreas ;
Gelenbe, Erol ;
Di Girolamo, Marco ;
Giuliani, Giovanni ;
De Meer, Hermann ;
Dang, Minh Quan ;
Pentikousis, Kostas .
COMPUTER JOURNAL, 2010, 53 (07) :1045-1051
[4]  
Chiwewe TM, 2016, IEEE INTL CONF IND I, P58, DOI 10.1109/INDIN.2016.7819134
[5]  
Husni E, 2016, 2016 INTERNATIONAL SEMINAR ON INTELLIGENT TECHNOLOGY AND ITS APPLICATIONS (ISITIA): RECENT TRENDS IN INTELLIGENT COMPUTATIONAL TECHNOLOGIES FOR SUSTAINABLE ENERGY, P417, DOI 10.1109/ISITIA.2016.7828696
[6]  
Jha M., 2015, 2015 IEEE First International Smart Cities Conference (ISC2), P1, DOI DOI 10.1109/ISC2.2015.7366153
[7]  
Liu X., 2016, Global Communications Conference (GLOBECOM), 2016 IEEE, P1
[8]  
Marinov MB, 2016, INT SPR SEM ELECT TE, P443, DOI 10.1109/ISSE.2016.7563237
[9]   Provisioning Software-defined IoT Cloud Systems [J].
Nastic, Stefan ;
Sehic, Sanjin ;
Duc-Hung Le ;
Hong-Linh Truong ;
Dustdar, Schahram .
2014 INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD (FICLOUD), 2014, :288-295
[10]  
Nayyar A, 2016, PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT, P1485