Cited by 50IoT-based Smart Home SystemsBuilding Energy and Comfort OptimizationArduino and IoT Applications

Elemental: An Open-Source Wireless Hardware and Software Platform for Building Energy and Indoor Environmental Monitoring and Control

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Ali, Akram Syed, Coté, Christopher, Heidarinejad, Mohammad, Stephens, Brent·2019·Sensors

Abstract

This work demonstrates an open-source hardware and software platform for monitoring the performance of buildings, called Elemental, that is designed to provide data on indoor environmental quality, energy usage, HVAC operation, and other factors to its users. It combines: (i) custom printed circuit boards (PCBs) with RFM69 frequency shift keying (FSK) radio frequency (RF) transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi 3B with custom firmware acting as either a centralized or distributed backhaul, and (iii) a custom dockerized application for the backend called Brood that serves as the director software managing message brokering via Message Queuing Telemetry Transport (MQTT) protocol using VerneMQ, database storage using InfluxDB, and data visualization using Grafana. The platform is built around the idea of a private, secure, and open technology for the built environment. Among its many applications, the platform allows occupants to investigate anomalies in energy usage, environmental quality, and thermal performance via a comprehensive dashboard with rich querying capabilities. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls or to provide recommendations on how to increase operational efficiency or improve operating conditions. Here, we demonstrate three distinct applications of the Elemental platform, including: (1) deployment in a research lab for long-term data collection and automated analysis, (2) use as a full-home energy and environmental monitoring solution, and (3) fault and anomaly detection and diagnostics of individual building systems at the zone-level. Through these applications we demonstrate that the platform allows easy and virtually unlimited datalogging, monitoring, and analysis of real-time sensor data with low setup costs. Low-power sensor nodes placed in abundance in a building can also provide precise and immediate fault-detection, allowing for tuning equipment for more efficient operation and faster maintenance during the lifetime of the building.

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References 40 · Cited by 50

Research works printed but not linked: 1

  1. [10]Bhunia S.S. Roy S. Mukherjee N. IEMS: Indoor environment monitoring system using ZigBee wireless sensor network Proceedings of the 2011 International Conference on Communication, Computing & Security—ICCCS ’11 Rourkela, Odisha, India 12–14 February 2011 ACM Press Rourkela, Odisha, India 2011 142

Authors
Ali, A. S., Coté, C., Heidarinejad, M., & Stephens, B.
Affiliations
  • Illinois Institute of Technology (US)
  • Entropealabs, Chicago, IL 60626, USA
Corresponding author
  • Ali, Akram Syed
  • Stephens, Brent
Venue
Sensors
Publisher
MDPI AG
Published
2019-09-18
Volume
19
Issue
18
Pages
4017
ISSN
1424-8220 (ISSN-L)
OpenAlex
W2974059810
Cited by
50
References
40
Citations by year
2025: 5 · 2024: 3 · 2023: 9 · 2022: 15 · 2021: 9 · 2020: 7 · 2019: 2
FWCI
2.97
Type
journal article
Language
en
Open access
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Franklin Energy (n/a)
  • American Society of Heating, Refrigerating and Air-Conditioning Engineers (New Investigator Award)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT-based Smart Home Systems
  • Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Arduino and IoT Applications
Keywords
open-source hardware, wireless sensor networks, building energy monitoring, indoor environmental quality, HVAC control, Raspberry Pi, MQTT, InfluxDB, Grafana, fault detection, anomaly detection, home energy monitoring, low-power sensor nodes

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