scholarly journals Numerical Model for Prediction of Indoor COVID-19 Infection Risk Based on Sensor Data

2021 ◽  
Vol 2069 (1) ◽  
pp. 012189
Author(s):  
J Virbulis ◽  
M Sjomkane ◽  
M Surovovs ◽  
A Jakovics
Keyword(s):  
Numerical Model ◽  
Low Cost ◽  
Infection Risk ◽  
Sensor Data ◽  
Effect Of Temperature ◽  
Indoor Environments ◽  
Building Management ◽  
Building Management System ◽  
Predicted Risk ◽  
Droplet Transmission

Abstract In addition to infection with SARS-CoV-2 via direct droplet transmission or contact with contaminated surfaces, infection via aerosol transport is a predominant pathway in indoor environments. The developed numerical model evaluates the risk of a COVID-19 infection in a particular room based on measurements of temperature, humidity, CO2 and particle concentration, the number of people and instances of speech, coughs and sneezing using a dedicated low-cost sensor system. The model can dynamically provide the predicted risk of infection to the building management system or people in the room. The effect of temperature, humidity and ventilation intensity on the infection risk is shown. Coughing and especially sneezing greatly increase the probability of infection in the room; therefore distinguishing these events is crucial for the applied measurement system.

scholarly journals Motion and Sash Height (MASH) alarms for efficient fume hood use

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Johnathan Kongoletos ◽  
Ethan Munden ◽  
Jennifer Ballew ◽  
Daniel J. Preston
Keyword(s):  
Low Cost ◽  
Energy Costs ◽  
Monitoring Device ◽  
Fume Hood ◽  
Energy Expenditures ◽  
Building Management ◽  
Active Feedback ◽  
Annual Carbon ◽  
Building Management System ◽  
Using Data

AbstractVentilation, including fume hoods, consumes 40–70% of the total energy used by modern laboratories. Energy-conscious fume hood usage—for example, closing the sash when a hood is unused—can significantly reduce energy expenditures due to ventilation. Prior approaches to promote such behaviors among lab users have primarily relied on passive feedback methods. In this work, we developed a low-cost fume hood monitoring device with active feedback to alert lab users when a fume hood is left open and unused. Using data collected by the building management system, we observed a 75.6% decrease in the average sash height after installation of these “Motion and Sash Height” (MASH) alarms, which would result in a reduction roughly equal to 43% of the annual carbon emissions of a typical American vehicle, for each fume hood. The MASH alarm presented here reduced energy costs by approximately $1,159 per year, per hood, at MIT.

A solution for annotating sensor data streams - An industrial use case in building management system

2020 ◽  
Author(s):  
Dumindu Madithiyagasthenna ◽  
Prem Prakash Jayaraman ◽  
Ahsan Morshed ◽  
Abdur Rahim Mohammad Forkan ◽  
Dimitrios Georgakopoulos ◽  
...  
Keyword(s):  
Data Streams ◽  
Management System ◽  
Sensor Data ◽  
Use Case ◽  
Building Management ◽  
Building Management System ◽  
Industrial Use

scholarly journals Full IoT Lora School Building Management System

2019 ◽  
Author(s):  
Bruno Mataloto ◽  
Joao C. Ferreira ◽  
Nuno Cruz
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Development Phase ◽  
Total Energy Consumption ◽  
Cooling Systems ◽  
Flexible Approach ◽  
Heating And Cooling ◽  
Building Management ◽  
Building Management System ◽  
Communication Board

In this research paper we describe the development phase of a low-cost LoRa IoT solution applied to a kindergarten school with three years results. A set of sensors solution was developed in a LoRa communication board, battery powered, providing a simplified setup process. These sensors were used in order to measure temperature, humidity, luminosity, air quality and presence. Also, energy monitor solutions were integrated. The acquired data is transmitted and analysed for knowledge extraction, identifying savings and other related KPIs. From data, automatic saving actions were performed towards heating and cooling systems, lighting and a set of if-then actions were developed for automatic cost-saving actions, based on infrared signals to heating/cooling systems using some procedure of external command devices. This approach avoids the usage of proprietary vendor solutions in a flexible approach that can easily be deployed to any building facility. This is an important achievement since most of the building consumption is based on heating and cooling systems. In a three years test of the solution, the total energy consumption savings surpassed 20%

scholarly journals PROGRESS ON ISPRS BENCHMARK ON MULTISENSORY INDOOR MAPPING AND POSITIONING

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1709-1713
Author(s):  
C. Wang ◽  
Y. Dai ◽  
N. El-Sheimy ◽  
C. Wen ◽  
G. Retscher ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Indoor Positioning ◽  
Benchmark Dataset ◽  
Scanning System ◽  
Indoor Environments ◽  
Building Management ◽  
Common Framework

<p><strong>Abstract.</strong> This paper presents the design of the benchmark dataset on multisensory indoor mapping and position (MIMAP) which is sponsored by ISPRS scientific initiatives. The benchmark dataset including point clouds captured by indoor mobile laser scanning system (IMLS) in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) SLAM-based indoor point cloud generation; (2) automated BIM feature extraction from point clouds, with an emphasis on the elements, such as floors, walls, ceilings, doors, windows, stairs, lamps, switches, air outlets, that are involved in building management and navigation tasks ; and (3) low-cost multisensory indoor positioning, focusing on the smartphone platform solution. MIMAP provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone indoor positioning methods.</p>

scholarly journals Exhaled CO2 as COVID-19 infection risk proxy for different indoor environments and activities

2020 ◽  
Author(s):  
Zhe Peng ◽  
Jose L Jimenez
Keyword(s):  
Respiratory Diseases ◽  
Low Cost ◽  
Infection Risk ◽  
Transmission Risk ◽  
Indoor Environments ◽  
Infected People ◽  
Risk Monitoring ◽  
Co2 Level ◽  
Analytical Expressions ◽  
Practical Recommendations

CO2 is co-exhaled with aerosols containing SARS-CoV-2 by COVID-19 infected people and can be used as a proxy of SARS-CoV-2 concentrations indoors. Indoor CO2 measurements by low-cost sensors hold promise for mass monitoring of indoor aerosol transmission risk for COVID-19 and other respiratory diseases. We derive analytical expressions of CO2-based risk proxies and apply them to various typical indoor environments. Contrary to some earlier recommendations setting a single indoor CO2 threshold, we show that the CO2 level corresponding to a given infection risk varies by over 2 orders of magnitude for different environments and activities. Although large uncertainties, mainly from virus exhalation rates, are still associated with our infection risk estimates, our study provides more specific and practical recommendations for low-cost CO2-based indoor infection risk monitoring.

scholarly journals Peel-and-Stick Sensors Powered by Directed RF Energy

2017 ◽  
Author(s):  
Christopher Lalau-Keraly ◽  
George Daniel ◽  
Joseph Lee ◽  
David Schwartz
Keyword(s):  
Wireless Sensors ◽  
High Performance ◽  
Energy Savings ◽  
Low Cost ◽  
Power Delivery ◽  
Sensor Nodes ◽  
Sensor Localization ◽  
Building Management ◽  
Building Management System ◽  
Rf Energy

PARC, a Xerox Company, is developing a low-cost system of peel-and-stick wireless sensors that will enable widespread building environment sensor deployment with the potential to deliver up to 30% energy savings. The system is embodied by a set of RF hubs that provide power to automatically located sensor nodes, and relay data wirelessly to the building management system (BMS). The sensor nodes are flexible electronic labels powered by rectified RF energy transmitted by an RF hub and can contain multiple printed and conventional sensors. The system design overcomes limitations in wireless sensors related to power delivery, lifetime, and cost by eliminating batteries and photovoltaic devices. Sensor localization is performed automatically by the inclusion of a programmable multidirectional antenna array in the RF hub. Comparison of signal strengths while the RF beam is swept allows for sensor localization, reducing installation effort and enabling automatic recommissioning of sensors that have been relocated, overcoming a significant challenge in building operations. PARC has already demonstrated wireless power and temperature data transmission up to a distance of 20m with less than one minute between measurements, using power levels well within the FCC regulation limits in the 902–928 MHz ISM band. The sensor’s RF energy harvesting antenna achieves high performance with dimensions below 5cm × 9cm.

scholarly journals Monitoring Indoor People Presence in Buildings Using Low-Cost Infrared Sensor Array in Doorways

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4062
Author(s):  
Cristian Perra ◽  
Amit Kumar ◽  
Michele Losito ◽  
Paolo Pirino ◽  
Milad Moradpour ◽  
...  
Keyword(s):  
Low Cost ◽  
Synthetic Data ◽  
Field Evaluation ◽  
Sensor Data ◽  
Indoor Environments ◽  
Stress Tests ◽  
Ambient Conditions ◽  
Time Pattern ◽  
Array Sensor ◽  
Depth Analysis

We propose a device for monitoring the number of people who are physically present inside indoor environments. The device performs local processing of infrared array sensor data detecting people’s direction, which allows monitoring users’ occupancy in any space of the building and also respects people privacy. The device implements a novel real-time pattern recognition algorithm for processing data sensed by a low-cost infrared (IR) array sensor. The computed information is transferred through a Z-Wave network. On-field evaluation of the algorithm has been conducted by placing the device on top of doorways in offices and laboratory rooms. To evaluate the performance of the algorithm in varying ambient temperatures, two groups of stress tests have been designed and performed. These tests established the detection limits linked to the difference between the average ambient temperature and perturbation. For an in-depth analysis of the accuracy of the algorithm, synthetic data have been generated considering temperature ranges typical of a residential environment, different human walking speeds (normal, brisk, running), and distance between the person and the sensor (1.5 m, 5 m, 7.5 m). The algorithm performed with high accuracy for routine human passage detection through a doorway, considering indoor ambient conditions of 21–30 °C.

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