IoT*(Ambisense): Smart environment monitoring using LoRa

In this work, IoT* (AmbiSense), we present our developed IoT system as a solution for Building and Energy Management using visualization tools to identify heuristics and create automatic savings. Our developed prototypes communicate using LoRa, one of the latest IoT technologies, and are composed of...

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Bibliographic Details
Main Author: Mataloto, Bruno Miguel Gonçalves (author)
Format: masterThesis
Language:eng
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10071/20267
Country:Portugal
Oai:oai:repositorio.iscte-iul.pt:10071/20267
Description
Summary:In this work, IoT* (AmbiSense), we present our developed IoT system as a solution for Building and Energy Management using visualization tools to identify heuristics and create automatic savings. Our developed prototypes communicate using LoRa, one of the latest IoT technologies, and are composed of a set of battery-operated sensors tied to a System on Chip. These sensors acquire environmental data such as temperature, humidity, luminosity, air quality, and also motion. For small to medium-size buildings where system management is possible, a multiplatform dashboard provides visualization templates with real-time data, allowing to identify patterns and extract heuristics that lead to savings using a set of pre-defined actions or manual intervention. LoBEMS (LoRa Building and Energy Management System), was validated in a kindergarten school during a three-year period. As an outcome, the evaluation of the proposed platform resulted in a 20% energy saving and a major improvement of the environment quality and comfort inside the school. For larger buildings where system management is not possible, we created a 3D visualization tool, that presents the system collected data and warnings in an interactive model of the building. This scenario was validated at ISCTE-IUL University Campus, where it was necessary to introduce the community interaction to achieve savings. As a requested application case, our system was also validated at the University Data Center, where the system templates were used to detect anomalies and suggest changes. Our flexible system approach can easily be deployed to any building facility without requiring large investments or complex system deployments.