Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to meet recent challenges for more efficient and economic industrial manufacturing plants and processes, new and already existing infrastructure is undergoing a transformation towards so called Smart Factories. The technologoies and approaches developed also have application outside of manufacturing, including agriculture. This paper introduces a fully integrated Data Analytics Infrastructure that can be used to transfer and store relevant sensor data from microcontrollers. This is applied to a prototype plant monitoring system using a Raspberry Pi as a processor and an IoT Cloud system for Real Time Application. The prototype implementation of the microcontroller integrates a temperature sensor, a humidity sensor, and a capacitive moisture sensor. The design uses a standalone ESP32 micro controller communicating to an MQTT Broker using the publish/subscribe method. Sensor data can be accessed by subscribing to the MQTT topic or by using the Web Application. The ESPlantMonitoring web application is developed for user management to grant access to the MQTT broker and view collected sensor data.
Original languageEnglish
Title of host publicationSmart City and Informatization
Subtitle of host publication7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings
EditorsGuojun Wang, Abdulmotaleb El Saddik, Xuejia Lia, Gregorio Martinez Perez, Kim-Kwang Raymond Choo
PublisherSpringer Singapore
Pages379-391
Number of pages13
Edition1st
ISBN (Electronic)9789811513015
ISBN (Print)9789811513008
DOIs
Publication statusE-pub ahead of print - 5 Nov 2019
Event7th International Conference on Smart City and Informatization - Guangzhou, China
Duration: 12 Nov 201915 Nov 2019
Conference number: 7
http://www.isci-conf.org/iSCI2019/

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer Nature Singapore Pte Ltd
Volume1122 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference7th International Conference on Smart City and Informatization
Abbreviated titleiSCI 2019
CountryChina
CityGuangzhou
Period12/11/1915/11/19
Internet address

Fingerprint

Process monitoring
Agriculture
Sensors
Microcontrollers
Industrial economics
Humidity sensors
Temperature sensors
Industrial plants
Moisture
Controllers
Monitoring

Cite this

Clarke, D., Al-Aqrabi, H., Hill, G., Mistry, P., & Lane, P. (2019). Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture. In G. Wang, A. El Saddik, X. Lia, G. Martinez Perez, & K-K. R. Choo (Eds.), Smart City and Informatization: 7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings (1st ed., pp. 379-391). (Communications in Computer and Information Science; Vol. 1122 CCIS). Springer Singapore. https://doi.org/10.1007/978-981-15-1301-5_30
Clarke, Daniel ; Al-Aqrabi, Hussain ; Hill, Graham ; Mistry, Pritesh ; Lane, Philip. / Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture. Smart City and Informatization: 7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings. editor / Guojun Wang ; Abdulmotaleb El Saddik ; Xuejia Lia ; Gregorio Martinez Perez ; Kim-Kwang Raymond Choo. 1st. ed. Springer Singapore, 2019. pp. 379-391 (Communications in Computer and Information Science).
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title = "Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture",
abstract = "In order to meet recent challenges for more efficient and economic industrial manufacturing plants and processes, new and already existing infrastructure is undergoing a transformation towards so called Smart Factories. The technologoies and approaches developed also have application outside of manufacturing, including agriculture. This paper introduces a fully integrated Data Analytics Infrastructure that can be used to transfer and store relevant sensor data from microcontrollers. This is applied to a prototype plant monitoring system using a Raspberry Pi as a processor and an IoT Cloud system for Real Time Application. The prototype implementation of the microcontroller integrates a temperature sensor, a humidity sensor, and a capacitive moisture sensor. The design uses a standalone ESP32 micro controller communicating to an MQTT Broker using the publish/subscribe method. Sensor data can be accessed by subscribing to the MQTT topic or by using the Web Application. The ESPlantMonitoring web application is developed for user management to grant access to the MQTT broker and view collected sensor data.",
keywords = "Smart Agriculture, Internet of Things, Cloud computing, Distributed Systems, Rasberry Pi, Arduino",
author = "Daniel Clarke and Hussain Al-Aqrabi and Graham Hill and Pritesh Mistry and Philip Lane",
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Clarke, D, Al-Aqrabi, H, Hill, G, Mistry, P & Lane, P 2019, Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture. in G Wang, A El Saddik, X Lia, G Martinez Perez & K-KR Choo (eds), Smart City and Informatization: 7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings. 1st edn, Communications in Computer and Information Science, vol. 1122 CCIS, Springer Singapore, pp. 379-391, 7th International Conference on Smart City and Informatization, Guangzhou, China, 12/11/19. https://doi.org/10.1007/978-981-15-1301-5_30

Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture. / Clarke, Daniel; Al-Aqrabi, Hussain; Hill, Graham; Mistry, Pritesh; Lane, Philip.

Smart City and Informatization: 7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings. ed. / Guojun Wang; Abdulmotaleb El Saddik; Xuejia Lia; Gregorio Martinez Perez; Kim-Kwang Raymond Choo. 1st. ed. Springer Singapore, 2019. p. 379-391 (Communications in Computer and Information Science; Vol. 1122 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - In order to meet recent challenges for more efficient and economic industrial manufacturing plants and processes, new and already existing infrastructure is undergoing a transformation towards so called Smart Factories. The technologoies and approaches developed also have application outside of manufacturing, including agriculture. This paper introduces a fully integrated Data Analytics Infrastructure that can be used to transfer and store relevant sensor data from microcontrollers. This is applied to a prototype plant monitoring system using a Raspberry Pi as a processor and an IoT Cloud system for Real Time Application. The prototype implementation of the microcontroller integrates a temperature sensor, a humidity sensor, and a capacitive moisture sensor. The design uses a standalone ESP32 micro controller communicating to an MQTT Broker using the publish/subscribe method. Sensor data can be accessed by subscribing to the MQTT topic or by using the Web Application. The ESPlantMonitoring web application is developed for user management to grant access to the MQTT broker and view collected sensor data.

AB - In order to meet recent challenges for more efficient and economic industrial manufacturing plants and processes, new and already existing infrastructure is undergoing a transformation towards so called Smart Factories. The technologoies and approaches developed also have application outside of manufacturing, including agriculture. This paper introduces a fully integrated Data Analytics Infrastructure that can be used to transfer and store relevant sensor data from microcontrollers. This is applied to a prototype plant monitoring system using a Raspberry Pi as a processor and an IoT Cloud system for Real Time Application. The prototype implementation of the microcontroller integrates a temperature sensor, a humidity sensor, and a capacitive moisture sensor. The design uses a standalone ESP32 micro controller communicating to an MQTT Broker using the publish/subscribe method. Sensor data can be accessed by subscribing to the MQTT topic or by using the Web Application. The ESPlantMonitoring web application is developed for user management to grant access to the MQTT broker and view collected sensor data.

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KW - Distributed Systems

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KW - Arduino

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M3 - Conference contribution

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T3 - Communications in Computer and Information Science

SP - 379

EP - 391

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A2 - Lia, Xuejia

A2 - Martinez Perez, Gregorio

A2 - Choo, Kim-Kwang Raymond

PB - Springer Singapore

ER -

Clarke D, Al-Aqrabi H, Hill G, Mistry P, Lane P. Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture. In Wang G, El Saddik A, Lia X, Martinez Perez G, Choo K-KR, editors, Smart City and Informatization: 7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings. 1st ed. Springer Singapore. 2019. p. 379-391. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-15-1301-5_30