Real-Time Air Pollution Monitoring Systems Using Wireless Sensor Networks Connected in a Cloud-Computing, Wrapped up Web Services

  • Byron Guanochanga
  • Rolando Cachipuendo
  • Walter FuertesEmail author
  • Santiago Salvador
  • Diego S. Benítez
  • Theofilos Toulkeridis
  • Jenny Torres
  • César Villacís
  • Freddy Tapia
  • Fausto Meneses
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 880)


Air pollution continues to grow at an alarming rate, decreasing the quality of life around the world. As part of preventive measures, this paper presents the design and implementation of a secure and low-cost real-time air pollution monitoring system. In such sense, a three-layer architecture system was implemented. The first layer contains sensors connected to an Arduino platform towards the data processing node (Raspberry’s Pi), which through a wireless network sends messages, using the Message Queuing Telemetry Transport (MQTT) protocol. As a failback method, strings are stored within the data processing nodes within flat files, and sent via SSH File Transfer Protocol (SFTP) as a restore operation in case the MQTT message protocol fails. The application layer consists of a server published in the cloud infrastructure having an MQTT Broker service, which performs the gateway functions of the messages sent from the sensor layer. Information is then published within a control panel using the NODE-RED service, which allowed to draw communication flows and the use of the received information and its posterior storage in a No SQL database named “MongoDB”. Furthermore, a RESTFUL WEB service was shared in order to transmit the information for a posterior analysis. The client layer can be accessed from a Web browser, a PC or smartphone. The results demonstrate that the proposed message architecture is able to translate JSON strings sent by the Arduino-based sensor Nodes and the Raspberry Pi gateway node, information about several types of air contaminants have been effectively visualized using web services.


Air pollution IoT IaaS WSN Web services 



The authors would like to thank the financial support of the Ecuadorian Corporation for the Development of Research and the Academy (RED CEDIA) in the development of this work, under Project Grant CEPRA-XI-2017-13.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Byron Guanochanga
    • 1
  • Rolando Cachipuendo
    • 1
  • Walter Fuertes
    • 1
    Email author
  • Santiago Salvador
    • 1
  • Diego S. Benítez
    • 2
  • Theofilos Toulkeridis
    • 1
  • Jenny Torres
    • 3
  • César Villacís
    • 1
  • Freddy Tapia
    • 1
  • Fausto Meneses
    • 1
  1. 1.Universidad de las Fuerzas Armadas ESPESangolquíEcuador
  2. 2.Universidad San Francisco de Quito USFQQuitoEcuador
  3. 3.Escuela Politécnica NacionalQuitoEcuador

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