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Smart farm monitoring

Java 10.97% Gherkin 0.68% Shell 0.56% Dockerfile 0.14% HTML 0.23% CSS 9.41% JavaScript 77.04% Groovy 0.30% Python 0.66%
universidade-de-aveiro spring-boot java farm docker kafka kafka-streams mongodb jenkins-pipeline cucumber tick-stack elk-stack reactjs

smartfarm's Introduction

SmartFarm

Project presented in the Software Engineering course (Universidade de Aveiro), 2018.

The main goal was to develop a system capable of helping the farmers to monitor its farm, using different types of sensors. The system collects the data from the sensors in farms and shows them in real-time, also allowing to define alerts based on the data coming from the sensors.

The platform was made using SpringBoot (Java) and followed DevOps techniques. Several technologies were used to follow a micro-services arquitecture, like Docker, Kafka, Kafka streams, ReactJS, MongoDB, PostgreSQL, Jenkins, Cucumber, TICK Stack, ELK Stack, among others.

Daniela Simões
Diogo Daniel Ferreira
Diogo Filipe Ferreira
Luís Leira
Pedro Martins

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