scholarly journals BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings

2021 ◽  
Vol 13 (8) ◽  
pp. 4496
Author(s):  
Giuseppe Desogus ◽  
Emanuela Quaquero ◽  
Giulia Rubiu ◽  
Gianluca Gatto ◽  
Cristian Perra
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Application Programming Interface ◽  
Visual Programming ◽  
Information Modeling ◽  
Sensor Data ◽  
Time Data ◽  
Existing Building ◽  
Building Maintenance ◽  
Indoor Conditions

The low accessibility to the information regarding buildings current performances causes deep difficulties in planning appropriate interventions. Internet of Things (IoT) sensors make available a high quantity of data on energy consumptions and indoor conditions of an existing building that can drive the choice of energy retrofit interventions. Moreover, the current developments in the topic of the digital twin are leading the diffusion of Building Information Modeling (BIM) methods and tools that can provide valid support to manage all data and information for the retrofit process. This paper shows the aim and the findings of research focused on testing the integrated use of BIM methodology and IoT systems. A common data platform for the visualization of building indoor conditions (e.g., temperature, luminance etc.) and of energy consumption parameters was carried out. This platform, tested on a case study located in Italy, is developed with the integration of low-cost IoT sensors and the Revit model. To obtain a dynamic and automated exchange of data between the sensors and the BIM model, the Revit software was integrated with the Dynamo visual programming platform and with a specific Application Programming Interface (API). It is an easy and straightforward tool that can provide building managers with real-time data and information about the energy consumption and the indoor conditions of buildings, but also allows for viewing of the historical sensor data table and creating graphical historical sensor data. Furthermore, the BIM model allows the management of other useful information about the building, such as dimensional data, functions, characteristics of the components of the building, maintenance status etc., which are essential for a much more conscious, effective and accurate management of the building and for defining the most suitable retrofit scenarios.

scholarly journals Semantic Traffic Sensor Data: The TRAFAIR Experience

2020 ◽  
Vol 10 (17) ◽  
pp. 5882
Author(s):  
Federico Desimoni ◽  
Sergio Ilarri ◽  
Laura Po ◽  
Federica Rollo ◽  
Raquel Trillo-Lado
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Smart Cities ◽  
Low Cost ◽  
Semantic Annotation ◽  
Open Data ◽  
Transportation Systems ◽  
Sensor Data ◽  
Time Data ◽  
Future Evolution

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective.

scholarly journals Exploration of Indoor Barrier-Free Plane Intelligent Lofting System Combining BIM and Multi-Sensors

2020 ◽  
Vol 12 (20) ◽  
pp. 3306
Author(s):  
Zijian Zhang ◽  
Xiaojun Cheng ◽  
Bilian Yang ◽  
Dong Yang
Keyword(s):  
Remote Sensing ◽  
Construction Projects ◽  
Low Cost ◽  
Rapid Development ◽  
Information Modeling ◽  
Sensor Data ◽  
Measurement Unit ◽  
Single Chip ◽  
Free Plane ◽  
Barrier Free

Lofting is an essential part of construction projects and the high quality of lofting is the basis of efficient construction. However, the most common method of lofting currently which uses the total station in a multi-person cooperative way consumes much manpower and time. With the rapid development of remote sensing and robot technology, using robots instead of manpower can effectively solve this problem, but few scholars study this. How to effectively combine remote sensing and robots with lofting is a challenging problem. In this paper, we propose an intelligent lofting system for indoor barrier-free plane environment, and design a high-flexibility, low-cost autonomous mobile robot platform based on single chip microcomputer, Micro Electro Mechanical Systems-Inertial Measurement Unit (MEMS-IMU), wheel encoder, and magnetometer. The robot also combines Building Information Modeling (BIM) laser lofting instrument and WIFI communication technology to get its own position. To ensure the accuracy of localization, the kinematics model of Mecanum wheel robot is built, and Extended Kalman Filter (EKF) is also used to fuse multi-sensor data. It can be seen from the final experimental results that this system can significantly improve lofting efficiency and reduce manpower.

scholarly journals Novel Internet of Things Platform for In-Building Power Quality Submetering

2018 ◽  
Vol 8 (8) ◽  
pp. 1320 ◽  
Author(s):  
Manuel Alonso-Rosa ◽  
Aurora Gil-de-Castro ◽  
Ricardo Medina-Gracia ◽  
Antonio Moreno-Munoz ◽  
Eduardo Cañete-Carmona
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Power Quality ◽  
Integrated Circuit ◽  
Early Stage ◽  
Low Cost ◽  
Good Health ◽  
Quality Parameters ◽  
Mesh Network ◽  
Time Data

As the number of facilities adopting a Building Management System under the Industry 4.0 paradigm increases, it is critical to ensure the good health of their operations. Business continuity and uninterrupted operations are key requirements for any building, for which Power Quality and Supply Reliability sophisticated monitoring can play an extremely important role. Submetering, as opposed to bulk-metering, implies measuring power consumption for individual units or appliances in a building complex. An Internet of Things mesh network, which brings ubiquitous power quality submetering inside the entire facility, would be extremely beneficial for the management of the building thus ensuring seamless business operations. This work describes a novel low-cost Internet of Things sensor for measuring and analyzing power quality at the input of any individual Alternating Current (AC) appliance, providing an early detection and analysis system which controls those critical variables inside the facility and leads to anticipate faults with early-stage alerts based on on-time data streams treatment. Moreover, the recorded power quality parameters that are processed in the Cloud system can help to reduce energy consumption, as power quality disturbances can be automatically analyzed and even compared to standard values. The proposed Internet of Things sensor will help users to detect most power quality steady-state and events disturbances, while monitoring the energy consumption. This Internet of Things Power Quality sensor is built around a flexible microcontroller, which manages an energy metering Integrated Circuit (IC) through Serial Peripheral Interface (SPI), increasing its original capabilities by including new sophisticated software functionality. Additionally, it wirelessly communicates with a cloud-based Internet of Things Platform to allow the storage and supervision of the different power quality events for the entire facility. An example of the access to the data is also included.

scholarly journals Data Acquisition and Transmission System for Building Energy Consumption Monitoring

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Liang Zhao ◽  
Jili Zhang ◽  
Ruobing Liang
Keyword(s):  
Energy Consumption ◽  
Data Acquisition ◽  
Low Cost ◽  
Building Energy ◽  
Mass Storage ◽  
Building Energy Consumption ◽  
Time Data ◽  
Tcp Protocol ◽  
Consumption Data ◽  
Sd Card

Building energy consumption monitoring and management system have been developed widely in China in order to gain the real-time data of energy consumption in buildings for analyzing it in the next state work. This paper describes a low-cost and small-sized collector based on the STM32 microcontroller, which can be placed in a building easily to implement the work of data acquisition, storage, and transmission. The collector gathers the electricity, water, heat, and energy consumption data through the RS485 field bus and stores the data into an SD card with mass storage, finally, using Internet to finish the communication and transmission to data server through TCP protocol. The collector has been used in application for two years, and the results show that the system is reliable and stable.

scholarly journals A Roadmap to Integrate Digital Twins for Small and Medium-Sized Enterprises

2021 ◽  
Vol 11 (20) ◽  
pp. 9479
Author(s):  
Alim Yasin ◽  
Toh Yen Pang ◽  
Chi-Tsun Cheng ◽  
Miro Miletic
Keyword(s):  
Data Storage ◽  
Cyber Security ◽  
3D Model ◽  
Low Cost ◽  
Sensor Data ◽  
Time Data ◽  
Communication Framework ◽  
Temperature Detector ◽  
Physical Asset ◽  
Iot Devices

In the last decade, Australian SMEs are steadily becoming more digitally engaged, but they still face issues and barriers to fully adopt Industry 4.0 (I4.0). Among the tools that I4.0 encompasses, digital twin (DT) and digital thread (DTH) technologies hold significant interest and value. Some of the challenges are the lack of expertise in developing the communication framework required for data collection, processing, and storing; concerns about data and cyber security; lack of knowledge of the digitization and visualisation of data; and value generation for businesses from the data. This article aims to demonstrate the feasibility of DT implementation for small and medium-sized enterprises (SMEs) by developing a framework based on simple and low-cost solutions and providing insight and guidance to overcome technological barriers. To do so, this paper first outlines the theoretical framework and its components, and subsequently discusses a simplified and generalised DT model of a real-world physical asset that demonstrates how these components function, how they are integrated and how they interact with each other. An experimental scenario is presented to transform data harvested from a resistance temperature detector sensor connected with a WAGO 750-8102 Programmable Logic Controller for data storage and analysis, predictive simulation and modelling. Our results demonstrate that sensor data could be readily integrated from Internet-of-Things (IoT) devices and enabling DT technologies, where users could view real time data and key performance indicators (KPIs) in the form of a 3D model. Data from both the sensor and 3D model are viewable in a comprehensive history log through a database. Via this technological demonstration, we provide several recommendations on software, hardware, and expertise that SMEs may adopt to assist with their DT implementations.

scholarly journals An Efficient power utilization approach with secure data transmission to maximize the life time of wireless sensor network with the help of duty cycle mechanism

2018 ◽  
Vol 7 (12) ◽  
pp. 24433-24438
Author(s):  
Bhagyashree A V ◽  
Khaja Moinuddin
Keyword(s):  
Energy Consumption ◽  
Duty Cycle ◽  
Data Transmission ◽  
Cluster Head ◽  
Path Selection ◽  
Energy Utilization ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Time Data ◽  
Transmission Phase

Lifetime enhancement has always been a crucial issue as most of the wireless sensor networks (WSNs) operate in unattended environment where human access and monitoring are practically infeasible. Clustering is one of the most powerful techniques that can arrange the system operation in associated manner to attend the network scalability, minimize energy consumption and achieve prolonged network lifetime. An efficient path selection will reduce energy utilization on data transmission phase at this time data should be secure, by using RSA algorithm.  In this paper, clustering mechanism and improvement in security is proposed. These two methods are used to decrease the energy consumption at data transmission phase and ensuring the security of the sensor data over wireless sensor .Key based security mechanism is used to secure the data. To ensure that any energy consumption associated with the role of the cluster head (CH) is shared between the nodes, the cluster head (CH) role is alternated between the nodes using duty cycle mechanism.  

scholarly journals Evaluating the applicability of a low-cost sensor for measuring PM2.5 concentration in Ho Chi Minh city, Viet Nam

2019 ◽  
Vol 22 (3) ◽  
pp. 343-347
Author(s):  
Chi Doan Thien Nguyen ◽  
Hien Thi To
Keyword(s):  
Real Time ◽  
Strong Correlation ◽  
Low Cost ◽  
Gravimetric Method ◽  
Reference Method ◽  
Sensor Data ◽  
Ho Chi Minh City ◽  
Time Data ◽  
New Approach ◽  
Pm2.5 Concentration

Introduction: Continuous monitoring provides real-time data which is helpful for measuring air quality; however, these systems are often very expensive, especially for developing countries such as Vietnam. The use of low-cost sensors for monitoring air pollution is a new approach in Vietnam and this study assesses the utility of low-cost, light-scattering-based, particulate sensors for measuring PM2.5 concentrations in Ho Chi Minh City. Methods: The low-cost sensors were compared with both a Beta attenuation monitor (BAM) reference method and a gravimetric method during the rainy season period of October to December 2018. Results: The results showed that there was a very strong correlation between two low-cost sensors (R = 0.97, slope = 1.0), and that the sensor precision varied from 0 to 21.4% with a mean of 3.1%. Both one-minute averaged data and one-hour averaged data showed similar correlations between sensors and BAM (R2 = 0.62 and 0.69, respectively), while 24-hour averaged data showed excellent agreement (R2 = 0.95, slope = 1.05). In addition, we also found a strong correlation between those instruments and a gravimetric method using 24-hour averaged data. A linear regression was used to calibrate the 24-hour averaged sensor data and, once calibrated, the bias dropped to zero. Conclusion: These results show that low-cost sensors can be used for daily measurements of PM2.5 concentrations in Ho Chi Minh City. The effect of air conditions, such as temperature and humidity, should be conducted. Moreover, technical methods to improve time resolution of lowcost sensors need to be developed and applied in order to provide real-time measurements at an inexpensive cost.  

scholarly journals An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards—Case Study: Workplace Reopening

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 50
Author(s):  
Steve H. L. Liang ◽  
Sara Saeedi ◽  
Soroush Ojagh ◽  
Sepehr Honarparvar ◽  
Sina Kiaei ◽  
...  
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Low Cost ◽  
Heterogeneous Systems ◽  
Geospatial Data ◽  
Sensor Data ◽  
Contact Tracing ◽  
Time Data ◽  
Sensor Web

To safely protect workplaces and the workforce during and after the COVID-19 pandemic, a scalable integrated sensing solution is required in order to offer real-time situational awareness and early warnings for decision-makers. However, an information-based solution for industry reopening is ineffective when the necessary operational information is locked up in disparate real-time data silos. There is a lot of ongoing effort to combat the COVID-19 pandemic using different combinations of low-cost, location-based contact tracing, and sensing technologies. These ad hoc Internet of Things (IoT) solutions for COVID-19 were developed using different data models and protocols without an interoperable way to interconnect these heterogeneous systems and exchange data on people and place interactions. This research aims to design and develop an interoperable Internet of COVID-19 Things (IoCT) architecture that is able to exchange, aggregate, and reuse disparate IoT sensor data sources in order for informed decisions to be made after understanding the real-time risks in workplaces based on person-to-place interactions. The IoCT architecture is based on the Sensor Web paradigm that connects various Things, Sensors, and Datastreams with an indoor geospatial data model. This paper presents a study of what, to the best of our knowledge, is the first real-world integrated implementation of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) and IndoorGML standards to calculate the risk of COVID-19 online using a workplace reopening case study. The proposed IoCT offers a new open standard-based information model, architecture, methodologies, and software tools that enable the interoperability of disparate COVID-19 monitoring systems with finer spatial-temporal granularity. A workplace cleaning use case was developed in order to demonstrate the capabilities of this proposed IoCT architecture. The implemented IoCT architecture included proximity-based contact tracing, people density sensors, a COVID-19 risky behavior monitoring system, and the contextual building geospatial data.

scholarly journals Sensor Fusion and Convolutional Neural Networks for Indoor Occupancy Prediction Using Multiple Low-Cost Low-Resolution Heat Sensor Data

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1036
Author(s):  
Simon Arvidsson ◽  
Marcus Gullstrand ◽  
Beril Sirmacek ◽  
Maria Riveiro
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Sensor Data ◽  
Low Resolution ◽  
Real Time Processing ◽  
Privacy Concerns ◽  
Sensor Field ◽  
Heat Sensor ◽  
Occupancy Prediction ◽  
The Impact

Indoor occupancy prediction is a prerequisite for the management of energy consumption, security, health, and other systems in smart buildings. Previous studies have shown that buildings that automatize their heating, lighting, air conditioning, and ventilation systems through considering the occupancy and activity information might reduce energy consumption by more than 50%. However, it is difficult to use high-resolution sensors and cameras for occupancy prediction due to privacy concerns. In this paper, we propose a novel solution for predicting occupancy using multiple low-cost and low-resolution heat sensors. We suggest two different methods for fusing and processing the data captured from multiple heat sensors and we use a Convolutional Neural Network for predicting occupancy. We conduct experiments to assess both the performance of the proposed solutions and analyze the impact of sensor field view overlaps on the prediction results. In summary, our experimental results show that the implemented solutions show high occupancy prediction accuracy and real-time processing capabilities.

scholarly journals Normative Aspects of Nudging in the International Sphere

AJIL Unbound ◽  
2021 ◽  
Vol 115 ◽  
pp. 263-267
Author(s):  
Doron Teichman ◽  
Eyal Zamir
Keyword(s):  
Energy Consumption ◽  
Organ Donation ◽  
Low Cost ◽  
National Level ◽  
The Past ◽  
The People ◽  
Posthumous Organ Donation ◽  
Regulatory Problems

The use of nudges—“low-cost, choice-preserving, behaviorally informed approaches to regulatory problems”—has become quite popular at the national level in the past decade or so. Examples include changing the default concerning employees’ saving for retirement in a bid to encourage such saving; altering the default about consent to posthumous organ donation to increase the supply of organs for transplantation; and informing people about other people's energy consumption to spur them to reduce theirs. Nudges are therefore used to promote the welfare of the people being nudged, and of society at large. However, the use of nudges has sparked a lively normative debate. When turning to the international arena, new arguments for and against nudges can be raised. This essay focuses on the normative aspects of using nudges in the international arena.

Sign in / Sign up

Export Citation Format

Share Document