Application of Low-Cost Sensors for Building Monitoring: A Systematic Literature Review

Green IoT Event Detection for Carbon-Emission Monitoring in Sensor Networks

This research addresses the intersection of low-power microcontroller technology and binary classification of events in the context of carbon-emission reduction. The study introduces an innovative approach leveraging microcontrollers for real-time event detection in a homogeneous hardware/firmware manner and faced with limited resources. This showcases their efficiency in processing sensor data and reducing power consumption without the need for extensive training sets. Two case studies focusing on landfill CO2 emissions and home energy usage demonstrate the feasibility and effectiveness of this approach. The findings highlight significant power savings achieved by minimizing data transmission during non-event periods (94.8-99.8%), in addition to presenting a sustainable alternative to traditional resource-intensive AI/ML platforms that comparatively draw and produce 20,000 times the amount of power and carbon emissions, respectively.

Structural Health Monitoring Design and Performance Evaluation of a Middle-Span Bridge

Structural health monitoring (SHM) has attracted significant attention over the past two decades due to its ability to provide real-time insight into the condition of structures. Despite the development of several SHM systems for long-span bridges, which play a crucial role in the assessment of these structures, studies focusing on short- or middle-span bridges remain scarce. This research paper presents an efficient and practical bridge monitoring and warning system established on a middle-span bridge, a key crossroad bridge located in Shenzhen. The monitoring system consists of sensors and measuring points that collect a substantial amount of data, enabling the close monitoring of various operational indicators to facilitate the early detection of threshold exceedances. Based on this system, the subtle condition of the bridge can be evaluated, and the operational condition of the bridge can be studied through the comparative analysis of the collected data. Over four months of monitoring, data including the strain and creep of the main beam, the strain and settlement of piers and the crack width of the bridge body are observed. Furthermore, the real-time operational status of the bridge is analyzed and evaluated through the combination of the collected data and the structural finite element model.

Studying the impacts of test condition and nonoptimal positioning of the sensors on the accuracy of the in-situ U-value measurement

The non-destructive thermal characterization of building envelopes relies significantly on various factors such as climate conditions, monitoring devices used, indoor environment, and conditioning systems. In the case of both the temperature-based method (TBM) and heat flux meter (HFM) approaches, U-value is determined considering the ideal condition of steady state. However, it is challenging to accurately define the true thermal condition of buildings when monitoring is affected by inherent uncertainties of the chosen approach and inadequate instrumentation of building envelopes. This paper presents the outcomes of an experimental campaign, that aimed to evaluate the impact of incorrectly positioned exterior sensors, on the precision of U-value measurements. This study simultaneously employed the TBM and HFM approaches. To enhance the accuracy of the results, rigorous outlier detection and statistical analysis were employed on the data collected from three autonomous monitoring systems. The findings of this study revealed that the applied data analysis yielded more satisfactory results for the TBM approach compared to HFM. However, regardless of the approach used, the effectiveness of outlier detection relied heavily on the accuracy of the monitoring systems. When removing an individual outlier, the monitoring systems characterized with higher accuracies provided U-values that were closer to the theoretical values, than less accurate ones.

Low-Cost Technologies Used in Corrosion Monitoring

Globally, corrosion is the costliest cause of the deterioration of metallic and concrete structures, leading to significant financial losses and unexpected loss of life. Therefore, corrosion monitoring is vital to the assessment of structures' residual performance and for the identification of pathologies in early stages for the predictive maintenance of facilities. However, the high price tag on available corrosion monitoring systems leads to their exclusive use for structural health monitoring applications, especially for atmospheric corrosion detection in civil structures. In this paper a systematic literature review is provided on the state-of-the-art electrochemical methods and physical methods used so far for corrosion monitoring compatible with low-cost sensors and data acquisition devices for metallic and concrete structures. In addition, special attention is paid to the use of these devices for corrosion monitoring and detection for in situ applications in different industries. This analysis demonstrates the possible applications of low-cost sensors in the corrosion monitoring sector. In addition, this study provides scholars with preferred techniques and the most common microcontrollers, such as Arduino, to overcome the corrosion monitoring difficulties in the construction industry.

Using RPA for Performance Monitoring of Dynamic SHM Applications

Robotic Process Automation (RPA) is a source of growing applications in a number of industries both as an individual technology and as a complement to other technologies (such as Internet of Things (IoT)). RPA allows the automation of human activities on a computer, especially when these activities are repetitive and high in volume. RPA saves man-hours and increases the productive capacity of the processes. The application of RPA in civil engineering is still in its early stages, and there has been little work on the subject in the literature. This paper presents RPA technology, for the first time in the literature, as a long-term management, control, and auto fault correction process for a low-cost accelerometer that can be used in SHM applications. However, this process requires a significant number of man-hours to stay operational, given the architecture of its applications. With the application of an RPA implementation workflow formulated based on the Design Science Research Method (DSRM), the management and control of the data acquisition process of a low-cost accelerometer located on a structural column are automated and put into operation in this study. RPA also made it possible to automatically detect and notify users of errors in the process, restart the process, and bring the process back online every time errors occurred. In this way, an automated process was obtained that operated continually and freed up human labour.

A Practical Approach to Launch the Low-Cost Monitoring Platforms for Nearly Net-Zero Energy Buildings in Vietnam

Buildings with solar rooftops have become vital objects in the energy transition in Vietnam. In this context, the demand for research on energy management solutions to use energy efficiently and increase PV energy absorption capacity is rising. In this paper, we present a practical route to developing a low-cost monitoring platform to meet the building energy management in the country. First, our project built a monitoring architecture with high-density wireless sensors in an office building in Vietnam. Next, we discussed the influence of significant obstacles such as technical issues, users, and cost on the resilience and reliability of the monitoring system. Then, we proposed essential solutions for data quality improvement by testing sensors, detecting wireless sensor network errors, and compensating for data losses by embedding machine learning. We found the platform’s potential in developing a rich database of building characteristics and occupants. Finally, we proposed plans exploiting the data to reduce wasted energy in equipment operation, change user behaviors, and increase auto-consumption PV power. The effectiveness of the monitoring platform was an approximate 62% energy reduction in the first year. The results are a cornerstone for implementing advanced research as modeling and real-time optimal control toward nearly zero-energy buildings.

A Procedure for Precise Determination and Compensation of Lead-Wire Resistance of a Two-Wire Resistance Temperature Detector

A procedure for the precise determination and compensation of the lead-wire resistance of a resistance transducer is presented. The proposed technique is suitable for a two-wire resistance transducer, especially the resistance temperature detector (RTD). The proposed procedure provides a technique to compensate for the lead-wire resistance using a three-level pulse signal to excite the RTD via the long lead wire. In addition, the variation in the lead-wire resistance disturbed by the change in the ambient temperature can also be compensated by using the proposed technique. The determination of the lead-wire resistance from the proposed procedure requires a simple computation method performed by a digital signal processing unit. Therefore, the calculation of the RTD resistance and the lead-wire resistance can be achieved without the requirement of a high-speed digital signal processing unit. The proposed procedure is implemented on two platforms to confirm its effectiveness: the LabVIEW computer program and the microcontroller board. Experimental results show that the RTD resistance was accurately acquired, where the measured temperature varied from 0 °C to 300 °C and the lead-wire resistance varied from 0.2 Ω to 20 Ω, corresponding to the length of the 26 American wire gauge (AWG) lead wire from 1.5 m to 150 m. The average power dissipation to the RTD was very low and the self-heating of the RTD was minimized. The measurement error of the RTD resistance observed for pt100 was within ±0.98 Ω or ±0.27 °C when the lead wire of 30 m was placed in an environment with the ambient temperature varying from 30 °C to 70 °C. It is evident that the proposed procedure provided a performance that agreed with the theoretical expectation.

A Novel Data Acquisition System for Obtaining Thermal Parameters of Building Envelopes

Owing to the high energy consumption in the building sector, appraising the thermal performance of building envelopes is an increasing concern. Recently, a few in situ methodologies to diagnose the thermal parameters of buildings have been considered. However, because of their limitations such as low accuracy, limited number of measurements, and the high cost of monitoring devices, researchers are seeking a new alternative. In this study, a novel hyper-efficient Arduino transmittance-meter was introduced to overcome these limitations and determine the thermal parameters of building envelopes. Unlike conventional methodologies, the proposed transmittance-meter is based on synchronized measurements of different parameters necessary to estimate the transmittance parameter. To verify the applicability of the transmittance-meter, an experimental study was conducted wherein a temperature-controlled box model was thermally monitored, and the outputs of the transmittance-meter employed were compared with those captured by a commercial device. The results revealed a high level of reduction in cost and a low range of difference compared with the latter, thereby validating the applicability of the proposed thermal monitoring system.

Measuring Indoor Occupancy through Environmental Sensors: A Systematic Review on Sensor Deployment

The COVID-19 pandemic has changed our common habits and lifestyle. Occupancy information is valued more now due to the restrictions put in place to reduce the spread of the virus. Over the years, several authors have developed methods and algorithms to detect/estimate occupancy in enclosed spaces. Similarly, different types of sensors have been installed in the places to allow this measurement. However, new researchers and practitioners often find it difficult to estimate the number of sensors to collect the data, the time needed to sense, and technical information related to sensor deployment. Therefore, this systematic review provides an overview of the type of environmental sensors used to detect/estimate occupancy, the places that have been selected to carry out experiments, details about the placement of the sensors, characteristics of datasets, and models/algorithms developed. Furthermore, with the information extracted from three selected studies, a technique to calculate the number of environmental sensors to be deployed is proposed.

Dynamic Data Feeding into BIM for Facility Management: A Prototype Application to a University Building

Building information modelling (BIM) has demonstrated its potential as a solution providing support to a series of operations related to facility management (FM) through building data retrieval, analysis, and processing. However, some challenges to the effective adoption of BIM-centred FM information systems occur in their design and implementation, causing obstacles to usability. Among these challenges are the customization of the information structure for each application case, the dynamic character of data supporting building maintenance, and the range of FM specialities involved, frequently including persons who are not BIM experts. This paper presents a BIM–FM prototype to support operations and access updated environmental data for a university building. The two contributions of the developed prototype are its ability to register two types of dynamic data, namely, the regularly acquired environmental sensor information and the sporadic building intervention records, and the automation of the data feeding, updating, and retrieval processes, allowing a user-friendly environment for both BIM experts and non-BIM users. Exploring the BIM interoperability and the integration of plug-ins, the proposed solution enables the comprehensive registration of dynamic FM-related data in an updated model while being accessible to all the specialities involved in the building management operations, enhancing its usability as an integrated solution for data maintenance and retrieval.

Monitoring Approaches for New-Generation Energy Performance Certificates in Residential Buildings

In 2002, the Energy Performance of Building Directive (EPBD) introduced energy certification schemes to classify and compare building performances to support reaching energy efficiency targets by informing the different actors of the building sectors. However, since its implementation, the Energy Performance Certifications (EPCs) remained unexploited with limited impact on the energy savings targets. In this context, the EPC RECAST project aims at studying a new generation of EPCs with a focus on the residential sector. More in detail, the paper presents and frames a monitoring approach based on low-cost and non-invasive technology for real data collection in existing residential apartments/houses. The method is based on different levels of monitoring selected according to the typology of the building (e.g., detached house, apartment), services (e.g., centralized or local energy generation), and energy vectors (e.g., natural gas or electricity). Three different levels have been identified (named as: basic, medium, and advanced) and for each one, different plug and play monitoring sensor kits have been selected. Six representative pilot buildings have been identified and selected to verify the approach in general and, in particular, the sensors’ applicability and communication, the data reliability, and the monitoring platform. The presented work highlights, on the one hand, the general feasibility of the proposed monitoring approach; on the other, it highlights the difficulty of fully standardizing the sensors kits considering that each building/apartment has specific characteristics and constraints that have to be carefully analyzed. The use of the ultrasonic flow meters represents a good technical option for reducing the cost and the impact on the existing plant system; however, their installation must be verified considering that the logger needs to be powered and the sensors calibrated for collecting reliable data.

Low-Cost Sensors Accuracy Study and Enhancement Strategy

Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, reliable acquisition system based on Arduino technology can further reduce the price of data acquisition and monitoring, which can make long-term monitoring possible. This paper introduces a wireless Internet-based low-cost data acquisition system consisting of Raspberry Pi and several Arduinos as signal conditioners. This study investigates the beneficial impact of similar sensor combinations, aiming to improve the overall accuracy of several sensors with an unknown accuracy range. The paper then describes an experiment that gives valuable information about the standard deviation, distribution functions, and error level of various individual low-cost sensors under different environmental circumstances. Unfortunately, these data are usually missing and sometimes assumed in numerical studies targeting the development of structural system identification methods. A measuring device consisting of a total of 75 contactless ranging sensors connected to two microcontrollers (Arduinos) was designed to study the similar sensor combination theory and present the standard deviation and distribution functions. The 75 sensors include: 25 units of HC-SR04 (analog), 25 units of VL53L0X, and 25 units of VL53L1X (digital).