Low-Cost IoT LoRa®Solutions for Precision Agriculture Monitoring Practices

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Silva, N (Author) Other; Mendes, J (Author) Other; Silva, R (Author) Other; Filipe Neves Santos (Author) FEUP; Mestre, P (Author) Other; Serôdio, C (Author) Other; Morais, R (Author) Other

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 224-235

19th EPIA Conference on Artificial Intelligence, EPIA 2019

3 September 2019 through 6 September 2019

Indexing

ISI Web of Knowledge - 19 Citations

Scopus - 21 Citations

Other information

Authenticus ID: P-00R-02Q

DOI: 10.1007/978-3-030-30241-2_20

Abstract (EN): Emergent and established paradigms, such as the Internet of Things (IoT), cloud and fog/edge computing, together with increasingly cheaper computing technologies ¿ with very low power requirements, available to exchange data with increased efficiency ¿ and intelligent systems, have evolved to a level where it is virtually possible to create and deploy monitoring solutions, even in Precision Agriculture (PA) practices. In this work, LoRa®(Long Range) technology and LoRaWAN¿protocol, are tested in a Precision Viticulture (PV) scenario, using low-power data acquisition devices deployed in a vineyard in the UTAD University Campus, distanced 400 m away from the nearest gateway. The main goal of this work is to evaluate sensor data integration in the mySense environment, a framework aimed to systematize data acquisition procedures to address common PA/PV issues, using LoRa®technology. mySense builds over a 4-layer technological structure: sensor and sensor nodes, crop field and sensor networks, cloud services and front-end applications. It makes available a set of free tools based on the Do-It-Yourself (DIY) concept and enables the use of low-cost platforms to quickly prototype a complete PA/PV monitoring application. © Springer Nature Switzerland AG 2019.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12