TY - GEN
T1 - Real-time air pollution monitoring systems using wireless sensor networks connected in a cloud-computing, wrapped up web services
AU - Guanochanga, Byron
AU - Cachipuendo, Rolando
AU - Fuertes, Walter
AU - Salvador, Santiago
AU - Benítez, Diego S.
AU - Toulkeridis, Theofilos
AU - Torres, Jenny
AU - Villacís, César
AU - Tapia, Freddy
AU - Meneses, Fausto
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Air pollution
KW - IaaS
KW - IoT
KW - WSN
KW - Web services
UR - http://www.scopus.com/inward/record.url?scp=85055916805&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-02686-8_14
DO - 10.1007/978-3-030-02686-8_14
M3 - Contribución a la conferencia
AN - SCOPUS:85055916805
SN - 9783030026851
T3 - Advances in Intelligent Systems and Computing
SP - 171
EP - 184
BT - Proceedings of the Future Technologies Conference (FTC) 2018 - Volume 1
A2 - Bhatia, Rahul
A2 - Arai, Kohei
A2 - Kapoor, Supriya
PB - Springer Verlag
T2 - Future Technologies Conference, FTC 2018
Y2 - 15 November 2018 through 16 November 2018
ER -