Real-Time Carbon Dioxide Monitoring Based on IoT & Cloud Technologies

被引:18
作者
Ming, Fan Xiu [1 ]
Habeeb, Riyaz Ahamed Ariyaluran [1 ]
Nasaruddin, Fariza Hanum Binti Md [2 ]
Bin Gani, Abdullah [2 ]
机构
[1] Int Univ Malaya Wales, Fac Sci Technol Engn & Math, Kuala Lumpur, Malaysia
[2] Univ Malaya, Fac Comp Sci Informat Technol, Kuala Lumpur, Malaysia
来源
2019 8TH INTERNATIONAL CONFERENCE ON SOFTWARE AND COMPUTER APPLICATIONS (ICSCA 2019) | 2019年
关键词
Internet of things; cloud; environment monitoring;
D O I
10.1145/3316615.3316622
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In recent years, environment monitoring are of greater importance towards the area of climate monitoring, analysis, agricultural productivity management, quality assurance of water, air, alongside with other potential factors that are closely connected to industrial development and convenience of living. This research is motivated by creating awareness of smart home residents on indoor air quality, as well as providing insight of carbon dioxide emissions for industries and environmental organizations. This paper proposes an efficient solution towards environment monitoring of carbon dioxide integrated with Internet of Things capability and cloud computing technology. Aforementioned techniques will deliver highly accessible and real-time data visualization which would be greatly beneficial for Smart Homes efficiency of analysis actualization and counter-measures deployment. A monitoring architecture was developed to generate, accumulate, store and visualize carbon dioxide concentration using MQ135 carbon dioxide sensor, ESP8266 Wi-Fi module, Firebase Cloud Storage Service and Android mobile application Carbon Insight for data visualization. 2880 data points in the time frame of 10 days with a 30-second interval was collected, stored and visualized with the application of this system.
引用
收藏
页码:517 / 521
页数:5
相关论文
共 10 条
  • [1] Big Sensor Data Systems for Smart Cities
    Ang, Li-Minn
    Seng, Kah Phooi
    Zungeru, Adamu Murtala
    Ijemaru, Gerald K.
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2017, 4 (05): : 1259 - 1271
  • [2] Big Data Storage in the Cloud for Smart Environment Monitoring
    Fazio, M.
    Celesti, A.
    Puliafito, A.
    Villari, M.
    [J]. 6TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT-2015), THE 5TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2015), 2015, 52 : 500 - 506
  • [3] Fine G. F, 2010, SENSORS-BASEL, V10
  • [4] Friedlingstein P, 2014, NAT GEOSCI, V7, P709, DOI [10.1038/NGEO2248, 10.1038/ngeo2248]
  • [5] An intensive two-week study of an urban CO2 dome in Phoenix, Arizona, USA
    Idso, CD
    Idso, SB
    Balling, RC
    [J]. ATMOSPHERIC ENVIRONMENT, 2001, 35 (06) : 995 - 1000
  • [6] Mao X, 2012, 2012 P IEEE INFOCOM
  • [7] Internet-of-Things-Based Smart Cities: Recent Advances and Challenges
    Mehmood, Yasir
    Ahmad, Farhan
    Yaqoob, Ibrar
    Adnane, Asma
    Imran, Muhammad
    Guizani, Sghaier
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2017, 55 (09) : 16 - 24
  • [8] Ray P. P., 2016, EAI Endorsed Transactions on Internet of Things, V2
  • [9] Real-Time Indoor Carbon Dioxide Monitoring Through Cognitive Wireless Sensor Networks
    Spachos, Petros
    Hatzinakos, Dimitrios
    [J]. IEEE SENSORS JOURNAL, 2016, 16 (02) : 506 - 514
  • [10] Yasuda T., 2012, SENSORS-BASEL, V12, DOI [10.3390/s120303641, DOI 10.3390/S120303641]