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

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Smart City and Informatization (iSCI 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1122))

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Abstract

In order to meet recent challenges for more efficient and economic industrial manufacturing plants and processes, existing infrastructure is undergoing a digital transformation towards Smart Factories/Industry 4.0. These technologies and approaches also have applications outside of manufacturing, including agriculture. We introduce a fully integrated data analytics infrastructure that can be used to transfer and store relevant agricultural sensor data from microcontrollers. This is applied to a prototype plant monitoring system using a Raspberry Pi for data processing 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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Authors and Affiliations

  1. School of Computing and Engineering, University of Huddersfield, Huddersfield, UK

    Daniel Clarke, Hussain Al-Aqrabi, Richard Hill, Pritesh Mistry & Phil Lane

Authors
  1. Daniel Clarke
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  2. Hussain Al-Aqrabi
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  3. Richard Hill
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  4. Pritesh Mistry
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  5. Phil Lane
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Corresponding author

Correspondence to Hussain Al-Aqrabi .

Editor information

Editors and Affiliations

  1. Guangzhou University, Guangzhou, China

    Guojun Wang

  2. University of Ottawa, Ottawa, ON, Canada

    Abdulmotaleb El Saddik

  3. Shanghai Jiao Tong University, Shanghai, China

    Xuejia Lai

  4. University of Murcia, Murcia, Spain

    Gregorio Martinez Perez

  5. The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

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© 2019 Springer Nature Singapore Pte Ltd.

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Clarke, D., Al-Aqrabi, H., Hill, R., Mistry, P., Lane, P. (2019). Implementing a Lightweight Cloud-Based Process Monitoring Solution for Smart Agriculture. In: Wang, G., El Saddik, A., Lai, X., Martinez Perez, G., Choo, KK. (eds) Smart City and Informatization. iSCI 2019. Communications in Computer and Information Science, vol 1122. Springer, Singapore. https://doi.org/10.1007/978-981-15-1301-5_30

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  • DOI: https://doi.org/10.1007/978-981-15-1301-5_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1300-8

  • Online ISBN: 978-981-15-1301-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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