Evolution of RFID Applications in Construction: A Literature Review

Measuring Labor Input: Construction Activity Counting Using IMU on Hand Tools

Efficient measurement of labor input is a critical aspect of on-site control and management in construction projects, as labor input serves as the primary and direct determinant of project outcomes. However, conventional manual inspection methods are off-line, tedious, and fail to capture their effectiveness. To address this issue, this research presents a novel method that leverages Inertial Measurement Unit (IMU) sensors attached to hand tools during construction activities to measure labor input in a timely and precise manner. This approach encompasses three steps: temporal-spatial feature extraction, self-similarity matrix calculation, and local specific structure identification. The underlying principle is based on the hypothesis that repetitive use data from hand tools can be systematically collected, analyzed, and converted into quantitative measures of labor input by the automatic recognition of repetition patterns. To validate this concept and assess its feasibility for general construction activities, we developed a preliminary prototype and conducted a pilot study focusing on rotation counting for a screw-connection task. A comparative analysis between the ground truth and the predicted results obtained from the experiments demonstrates the effectiveness and efficiency of measuring labor input using IMU sensors on hand tools, with a relative error of less than 5%. To minimize the measurement error, further work is currently underway for accurate activity segmentation and fast feature extraction, enabling deeper insights into on-site construction behaviors.

Assessing Technology Implementation Success for Highway Construction and Asset Management

The increasing demand for safe, reliable, and higher-quality infrastructure systems has led to more complex transportation construction and maintenance projects. This, coupled with the declining staff levels at many transportation agencies, requires a more comprehensive evaluation of technology implementation to compensate for these challenges. With a focus on effective technology implementation, this research goes beyond simply evaluating technologies to investigate technology implementation with personnel and policies at departments of transportation (DOTs). The study methodology involved a comprehensive literature review, a survey of all 50 state DOTs, and an in-person workshop of 18 DOT experts to validate the survey results and preliminary research findings. The findings support the need for those implementing technologies to understand people, processes, and technology maturity for their improved chances of implementation success. Using the approach presented, the DOTs can assess themselves and identify pathways to higher maturity levels in the areas of their people, processes, and technologies. This study also highlighted six factors that are important considerations for technology implementation and thus determined the relative importance of people, processes, and technology for these factors. The objective of this study was to assess the importance of people, processes, and technology that DOTs should prioritize to enhance the likelihood of successfully implementing technologies. The framework presented herein can be extended to any new or existing technology implementation initiatives at a DOT, including automatic identification and data capture (AIDC), emerging sensing and wireless technologies, safety technologies, and others.

Prevention of Falls from Heights in Construction Using an IoT System Based on Fuzzy Markup Language and JFML

The main cause of fatal accidents in the construction sector are falls from height (FFH) and the inappropriate use of a harness is commonly associated with these fatalities. Traditional methods, such as onsite inspections, safety communication, or safety training, are not enough to mitigate accidents caused by FFH associated with a poor management in the use of a harness. Although some technological solutions for the automated monitoring of workers could improve safety conditions, their use is not frequent due to the particularities of construction sites: complexity, dynamic environments, outdoor workplaces, etc. Then, the integration of expert knowledge with technology is a key issue. Fuzzy logic systems (FLS) and Internet of Things (IoT) present many potential benefits, such as real-time decisions being made based on FLS and data from sensors. In the current research, the development and test of an IoT system integrated with the Java Fuzzy Markup Language Library for FLS, to support experts’ decision making in FFH, is proposed. The proposal was checked in four construction scenarios based on working conditions with different levels of risk of FFH and obtained promising results.

A Framework for Prefabricated Component Hoisting Management Systems Based on Digital Twin Technology

The hoisting of prefabricated components (PCs) is a key step during the construction of prefabricated buildings. Aiming at the problems existing in the control of PC hoisting, an innovative hoisting management system framework based on the digital twin (DT) is established in this paper. The system framework comprehensively utilizes the building information model (BIM) and Internet of Things (IoT) to establish a digital twin model (DTm) for PC hoisting control and uses Dijkstra’s algorithm to conduct hoisting route planning according to the BIM data in the model. Meanwhile, long-range radio (LoRa) technology was used for data acquisition and transmission to monitor the movement state of the PCs in the hoisting process. By testing it in a prefabricated building project, the DT control method was conducted to realize the functions of real-time information collection, hoisting path planning and PC positioning, which proved the feasibility and effectiveness of the method. As a key technology to realize intelligent manufacturing, DT has been widely studied in academia. The DTm of the hoisting process of PCs is established in this study; it improves the level of intelligent management of prefabricated building construction and provides a new idea for intelligent building construction.

Review on Sensing Technology Adoption in the Construction Industry

Sensing technologies demonstrate promising potential in providing the construction industry with a safe, productive, and high-quality process. The majority of sensing technologies in the construction research area have been focused on construction automation research in prefabrication, on-site operation, and logistics. However, most of these technologies are either not implemented in real construction projects or are at the very early stages in practice. The corresponding applications are far behind, even in extensively researched aspects such as Radio Frequency Identification, ultra-wideband technology, and Fiber Optic Sensing technology. This review systematically investigates the current status of sensing technologies in construction from 187 articles and explores the reasons responsible for their slow adoption from 69 articles. First, this paper identifies common sensing technologies and investigates their implementation extent. Second, contributions and limitations of sensing technologies are elaborated to understand the current status. Third, key factors influencing the adoption of sensing technologies are extracted from construction stakeholders' experience. Demand towards sensing technologies, benefits and suitability of them, and barriers to their adoption are reviewed. Lastly, the governance framework is determined as the research tendency facilitating sensing technologies adoption. This paper provides a theoretical basis for the governance framework development. It will promote the sensing technologies adoption and improve construction performance including safety, productivity, and quality.

Virtual Fence System Based on IoT Paradigm to Prevent Occupational Accidents in the Construction Sector

Many occupational accidents in construction sites are caused by the intrusion of a worker into a hazardous area. Technological solutions based on RFID, BIM, or UWB can reduce accidents, but they still have some limitations.The aim of the current paper is to design and evaluate a new system of “virtual fences” based on Bluetooth Low-Energy (BLE) to avoid intrusions. First of all, the system was designed using a number of beacons, a Bayesian filter, a finite state machine, and an indicator. Secondly, its safety attributes were evaluated based on a scientific questionnaire by an expert panel following the staticized groups’ methodology. Results showed that the proposal is inexpensive and easy to integrate and configure. The selected experts evaluated positively all the attributes of the system, and provided valuable insights for further improvements. From the experts’ discussions, we concluded that successful adoption of this “virtual fence” system based on BLE beacons should consider the influence of factors such as cost savings, top management support, social acceptance, and compatibility and integration with existing systems, procedures, and company culture. In addition, legislation updates according to technical advances would help with successful adoption of any new safety system.

Sensorial Multifunctional Panels for Smart Factory Applications

The use of Key Enabling Technologies (KET), in the definition of innovative systems, is a crucial point for smart industries and sustainability. The proposed work combines innovations from different fields, including industrial sustainability on the one hand, and smart electronics on the other. An innovative multifunctional panel is presented, produced with waste resulting from the industrial processing of paper and cardboard; the panel can be used for the control of safety in processing factories and for the monitoring of environmental conditions in the area, as well as the energy improvement of the building envelope. Several sensors are embedded in the panel for monitoring temperature, moisture, and localization by means of an RFID tag. In addition, the panel is battery–free, thus enhancing the installation and realization of the system. The power supply is provided by the tag reader as irradiated power, thus realizing a very low power application. Panels have been already realized and experimental tests have been performed in the laboratory.

RFID Applications and Security Review

Radio frequency identification (RFID) is widely used in several contexts, such as logistics, supply chains, asset tracking, and health, among others, therefore drawing the attention of many researchers. This paper presents a review of the most cited topics regarding RFID focused on applications, security, and privacy. A total of 62,685 records were downloaded from the Web of Science (WoS) and Scopus core databases and processed, reconciling the datasets to remove duplicates, resulting in 40,677 unique elements. Fundamental indicators were extracted and are presented, such as the citation number, average growth rate, and average number of documents per year. We extracted the top topics and reviewed the relevant indicators using a free Python tool, ScientoPy. The results are discussed in the following sections: the first is the Applications Section, whose subsections are the Internet of Things (IoT), Supply Chain Management, Localization, Traceability, Logistics, Ubiquitous Computing, Healthcare, and Access Control; the second is the Security and Privacy section, whose subsections are Authentication, Privacy, and Ownership Transfer; finally, we present the Discussion section. This paper intends to provide the reader with a global view of the current status of trending RFID topics and present different analyses from different perspectives depending on motivations or background.

Application of Lifecycle Measures for an Integrated Method of Environmental Sustainability Assessment of Radio Frequency Identification and Wireless Sensor Networks

Internet of Things (IoT) technology has advanced in recent years, leading to improvements of manufacturing processes. As a result of such improvements, environmental sustainability assessments for technologies have been requested by international control agencies. Although various assessment approaches are widely applied, IoT technology requires effective assessment methods to support the decision-making process and that incorporate qualitative measures to create quantifiable values. In this paper, a new environmental sustainability assessment method is developed to assess radio frequency identification (RFID) and wireless sensors networks (WSN). This integrated assessment method incorporates a modified and redesigned conceptual methodology based on technical project evaluation (IMATOV) and an extension of conventional lifecycle measures. The results shows the most and least important metrics. The most important metrics are the categories “electronic devices disposed of completely” and “decrease in stocks”, with the greatest GWFs (20% and 19%, respectively) and IAVs (127% and 117%, respectively) and moderate consolidated degrees of fulfillment. Relatively low degrees of fulfillment are achieved by categories such as “decrease in numbers of assets”, “supply chain echelons benefiting RFID”, and “tag lifecycle duration”, with IAVs below 10%. This study promotes an integrated method to support decision-making processes in the context of environmental sustainability assessments based on lifecycle measures.

Identification of Markers in Challenging Conditions for People with Visual Impairment Using Convolutional Neural Network

People with visual impairment face a lot of difficulties in their daily activities. Several researches have been conducted to find smart solutions using mobile devices to help people with visual impairment perform tasks. This paper focuses on using assistive technology to help people with visual impairment in indoor navigation using markers. The essential steps of a typical navigation system are identifying the current location, finding the shortest path to the destination, and navigating safely to the destination using navigation feedback. In this research, the authors proposed a system to help people with visual impairment in indoor navigation using markers. In this system, the authors have re-defined the identification step to a classification problem and used convolutional neural networks to identify markers. The main contributions of this paper are: (1) A system to help people with visual impairment in indoor navigation using markers. (2) Comparing QR codes with Aruco markers to prove that Aruco markers work better. (3) Convolutional neural network has been implemented and simplified to detect the candidate markers in challenging conditions and improve response time. (4) Comparing the proposed model with another model to prove that it gives better accuracy for training and testing.

Factors Affecting the Synthesis of Autonomous Sensors with RFID Interface

A general view on the problem of designing atypical battery-free, autonomous semi-passive RFID transponders-sensors (autonomous sensors with RFID interfaces) is presented in this review. Although RFID devices can be created in any of the electronic technologies, the design stage must be repeated each time when the manufacturing processes are changed, and their specific conditions have to be taken into consideration when modeling new solutions. Aspects related to the factors affecting the synthesis of semi-passive RFID transponder components on the basis of which the idea of the autonomous RFID sensor was developed are reflected in the paper. Besides their general characteristics, the operation conditions of modern RFID systems and achievements in autonomous RFID sensor technology are revealed in subsequent sections—they include such issues as technological aspects of the synthesis process, designing antennas for RFID transponders, determining RFID chip and antenna parameters, creating the interrogation zone IZ, etc. It should be pointed that the universal construction of an autonomous RFID sensor, which could be use in any application of the automatic object identification system, cannot be developed according to the current state of the art. Moreover, a trial and error method is the most commonly used in the today’s process of designing new solutions, and the basic parameters are estimated on the basis of the tests and the research team experience. Therefore, it is necessary to look for new inventions and methods in order to improve implementations of RFID systems.

Development of Intelligent Prefabs Using IoT Technology to Improve the Performance of Prefabricated Construction Projects

Prefabrication (PC) projects have many advantages, such as cost and energy savings and waste reduction. However, some problems still exist that hamper the development of prefabrication projects. To improve PC project performance and advance innovation in construction, this study introduces an innovative method that incorporates Radio Frequency Identification (RFID) and Long Range (LoRa) technologies, sensor networks, the BIM model and cloud computing to automatically collect, analyze and display real-time information about PC components. It can locate PC components on a construction site and monitor their structural performance during the installation process. RFID technology and strain sensors were used to collect the required data on a construction site. All the data was transmitted to a server using LoRa technology. Then, the cloud-based Building Information Modelling (BIM) model of the project was developed to store and vividly present project information and real-time onsite data. Moreover, the cloud-based BIM model enables project team members to access the project information from anywhere by using mobile devices. The proposed system was tested on a real PC project to validate its effectiveness. The results indicate that the sensor network can provide reliable data via LoRa technology, and a PC component can be accurately located on site. Also, the monitoring data of structural performance for the PC component during the installation process is acceptable. The proposed method using innovative technologies can improve PC project performance and help industry professionals by providing sufficient required information.

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

People with visual impairment face various difficulties in their daily activities in comparison to people without visual impairment. Much research has been done to find smart solutions using mobile devices to help people with visual impairment perform tasks like shopping. One of the most challenging tasks for researchers is to create a solution that offers a good quality of life for people with visual impairment. It is also essential to develop solutions that encourage people with visual impairment to participate in social life. This study provides an overview of the various technologies that have been developed in recent years to assist people with visual impairment in shopping tasks. It gives an introduction to the latest direction in this area, which will help developers to incorporate such solutions into their research.

The use of smart technologies in enabling construction components reuse: A viable method or a problem creating solution?

The exploitation of Radio Frequency Identification (RFID) for tracking and archiving the properties of structural construction components could be a potentially innovative disruption for the construction sector. This is because RFID can stimulate the reuse of construction components and reduce their wastage, hence addressing sustainability issues in the construction sector. To test the plausibility of that idea, this study explores the potential pre-conditions for RFID to facilitate construction components reuse, and develops a guidance for promoting their redistribution back to the supply chain. It also looks at how integrating RFID with Building Information Modelling (BIM) can possibly be a valuable extension of its capabilities, providing the opportunity for tracked components to be incorporated into new structures in an informed, sound way. A preliminary assessment of the strengths, weaknesses, opportunities and threats of the RFID technology is presented in order to depict its current and future potential in promoting construction components' sustainable lifecycle management, while emphasis has been laid on capturing their technical, environmental, economic and social value. Findings suggest that the collection of the right amount of information at the design-construction-deconstruction-reuse-disposal stage is crucial for RFID to become a successful innovation in the construction sector. Although a number of limitations related to the technical operability and recycling of RFID tags seem to currently hinder its uptake for structural components' lifecycle management, future technological innovations could provide solutions that would enable it to become a mainstream practice. Taken together these proposals advocate that the use of RFID and its integration with BIM can create the right environment for the development of new business models focused on sustainable resource management. These models may then unlock multiple values that are otherwise dissipated in the system. If the rapid technological development of RFID capability can be allied to policy interventions that control and manage its uptake along the supply chain, the sustainable lifecycle management of construction components could be radically enhanced.

Improving Efficiency of Passive RFID Tag Anti-Collision Protocol Using Dynamic Frame Adjustment and Optimal Splitting

Radio frequency identification is a wireless communication technology, which enables data gathering and identifies recognition from any tagged object. The number of collisions produced during wireless communication would lead to a variety of problems including unwanted number of iterations and reader-induced idle slots, computational complexity in terms of estimation as well as recognition of the number of tags. In this work, dynamic frame adjustment and optimal splitting are employed together in the proposed algorithm. In the dynamic frame adjustment method, the length of frames is based on the quantity of tags to yield optimal efficiency. The optimal splitting method is conceived with smaller duration of idle slots using an optimal value for splitting level Mopt, where (M > 2), to vary slot sizes to get the minimal identification time for the idle slots. The application of the proposed algorithm offers the advantages of not going for the cumbersome estimation of the quantity of tags incurred and the size (number) of tags has no effect on its performance efficiency. Our experiment results show that using the proposed algorithm, the efficiency curve remains constant as the number of tags varies from 50 to 450, resulting in an overall theoretical gain in the efficiency of 0.032 compared to system efficiency of 0.441 and thus outperforming both dynamic binary tree slotted ALOHA (DBTSA) and binary splitting protocols.

An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor

The Global Positioning System (GPS) is widely used in outdoor environmental positioning. However, GPS cannot support indoor positioning because there is no signal for positioning in an indoor environment. Nowadays, there are many situations which require indoor positioning, such as searching for a book in a library, looking for luggage in an airport, emergence navigation for fire alarms, robot location, etc. Many technologies, such as ultrasonic, sensors, Bluetooth, WiFi, magnetic field, Radio Frequency Identification (RFID), etc., are used to perform indoor positioning. Compared with other technologies, RFID used in indoor positioning is more cost and energy efficient. The Traditional RFID indoor positioning algorithm LANDMARC utilizes a Received Signal Strength (RSS) indicator to track objects. However, the RSS value is easily affected by environmental noise and other interference. In this paper, our purpose is to reduce the location fluctuation and error caused by multipath and environmental interference in LANDMARC. We propose a novel indoor positioning algorithm based on Bayesian probability and K-Nearest Neighbor (BKNN). The experimental results show that the Gaussian filter can filter some abnormal RSS values. The proposed BKNN algorithm has the smallest location error compared with the Gaussian-based algorithm, LANDMARC and an improved KNN algorithm. The average error in location estimation is about 15 cm using our method.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

Investigation of Interference Models for RFID Systems

The reader-to-reader collision in an RFID system is a challenging problem for communications technology. In order to model the interference between RFID readers, different interference models have been proposed, mainly based on two approaches: single and additive interference. The former only considers the interference from one reader within a certain range, whereas the latter takes into account the sum of all of the simultaneous interferences in order to emulate a more realistic behavior. Although the difference between the two approaches has been theoretically analyzed in previous research, their effects on the estimated performance of the reader-to-reader anti-collision protocols have not yet been investigated. In this paper, the influence of the interference model on the anti-collision protocols is studied by simulating a representative state-of-the-art protocol. The results presented in this paper highlight that the use of additive models, although more computationally intensive, is mandatory to improve the performance of anti-collision protocols.

Reusable EGaIn-Injected Substrate-Integrated-Waveguide Resonator for Wireless Sensor Applications

The proposed structure in this research is constructed on substrate integrated waveguide (SIW) technology and has a mechanism that produces 16 different and distinct resonant frequencies between 2.45 and 3.05 GHz by perturbing a fundamental TE₁₀ mode. It is a unique method for producing multiple resonances in a radio frequency planar structure without any extra circuitry or passive elements is developed. The proposed SIW structure has four vertical fluidic holes (channels); injecting eutectic gallium indium (EGaIn), also known commonly as liquid metal (LM), into these vertical channels produces different resonant frequencies. Either a channel is empty, or it is filled with LM. In total, the combination of different frequencies produced from four vertical channels is 16.