Secure indoor ranging is a critical component of modern industrial systems, with applications in access control, contactless payments, and industrial automation. This article presents the first comprehensive survey focusing exclusively on secure-ranging protocols for Bluetooth, ultrawideband (UWB), and Wi-Fi. Unlike localization, which relies on multiple anchors, ranging involves only two devices; therefore, popular attack detection methods based on multianchor data do not generalize to secure ranging. This article begins by detailing industry-standard protocols such as IEEE 802.15.4a for UWB, Bluetooth, and IEEE 802.11 for Wi-Fi, followed by an analysis of their vulnerabilities and distance manipulation attacks. Common attack strategies, including overshadow, early path injection, and relay attacks, are explored. To mitigate these threats, we review countermeasures grouped into two main categories: randomization and channel integrity verification, which incorporate techniques from machine learning, threshold-based anomaly detection, and cryptography. Finally, we highlight cross-technology insights, discuss lessons learned, and propose future research directions to address unresolved challenges in indoor-ranging security.

The increasing commercial viability of body area network (BAN) devices has expanded their applications beyond smartwatches and smartphones to include wearables for industrial safety, healthcare monitoring, and augmented reality systems. Secure communication between these devices remains a challenge, as traditional cryptographic key exchange protocols impose significant computational and power constraints. Physically Derived Symmetric Key (PDSK) generation offers a lightweight alternative by leveraging the shared wireless channel characteristics to establish encryption keys without prior trust. Recent studies have demonstrated the effectiveness of PDSK in ultra-wideband (UWB) systems, as UWB’s high-resolution channel measurements capture high-entropy yet highly correlated signal variations at different devices. In this work, we evaluate the feasibility of UWB-based PDSK in BAN wearable devices. Our results show that secret keys can be reliably generated, achieving a bit agreement rate (BAR) of 84.14% and a key success rate (KSR) of 92.7% while generating 240-bit keys in 0.35s. We further analyse key generation performance across different wearable placements and movement conditions, demonstrating that UWB-based PDSK is a viable and practical solution for secure communication in BAN applications.

NLOS and multipath propagation are the main hurdles for accurate localization with time-based localization systems. Over the years, researchers have proposed myriad approaches to mitigate the effects of Non-Line-of-Sight (NLOS) and multipath propagation for accurate indoor localization. Residual Weighting (Rwgh) is a widely used technique for NLOS mitigation in literature. This is because it does not require expensive site surveys or statistical information of the channel. Also, position estimation is possible even if all the nodes (anchors) are in NLOS. We observed that with Ultra-Wideband (UWB), the ranging results in Line-Of-Sight conditions are stable compared to NLOS and multipath ranging scenarios. Based on this, we propose a Rwgh approach by exploring the stability of the range measurements obtained during the localization phase. The stability of the range measurement gives an indication of the veracity of the introduced residuals, which is then weighted to mitigate the NLOS effects directly during localization. We test the performance of the proposed approach with data collected from two distinct real-world environments with heavy NLOS and multipath presence instead of simulated data as used in the preponderance of Rwgh-based approaches.

A major challenge to Ultra-Wideband (UWB) positioning, especially in indoor environments, is the prevalent presence of Non-Line-Of-Sight (NLOS) and multipath propagations, degrading localization performance. Moreover, indoor settings tend to constantly change, making it difficult to characterize NLOS signals each time these changes occur. Promising approaches have been proposed to identify NLOS signals before localization; however, their performance is limited to the specific environment where measurements were carried out and cannot be extended to new or different environments. This can be attributed to feature discrepancies causing domain shifts and distribution divergence, owing to differences in environments captured by the Channel Impulse Response (CIR) waveforms. In this paper, we propose a domain Adaptive NLOS (AdaLOS) identification framework for UWB positioning systems. First, adaptation knowledge is obtained to align the source and target domains’ CIRs to mitigate the domain shift problem via cross-domain mappings. The distribution gap of the CIRs is further reduced by minimizing the marginal and conditional distribution divergence between the two domains (environments) by employing the Maximum Mean Discrepancy (MMD) criterion. A joint optimization procedure is then formulated to minimize the domain shift, marginal, and conditional distribution differences between CIRs from the two domains simultaneously. After minimizing the domain difference, Transformed Representative Features (TRF) of the source and target domains are obtained to train a domain-invariant classifier. We perform extensive simulations with CIR information collected from four distinct indoor environments characterized by different relative permittivity, signal distortions, noise, etc. AdaLOS is effective in adapting to new, distinct environments and significantly outperforms state-of-the-art works for NLOS identification.

Physical layer key sharing has become a popular topic in today's literature, as it could provide an alternative to computationally expensive key-sharing protocols. Its importance is emphasized by several resource-constrained, battery-powered autonomous robots, and personal devices that must communicate within modern-day industrial complexes. Physical layer key sharing has been explored using temporally and spatially variant characteristics of signals to produce the same secret keys at different devices. In this paper, we propose a novel method for ultra-wideband (UWB)-based physical layer key sharing, leveraging an off-the-shelf plug-and-play UWB module and utilizing the frequency domain of the Channel Impulse Response (CIR) magnitude. The frequency domain effectively aligns and denoises CIR samples, increasing the spatial and temporal uniqueness of channel characteristics. In turn, our approach offers the advantage of creating high-entropy keys with a 92% success rate. Our paper is the first to examine employing an UWB module for key sharing under different dynamic scenarios. Finally, our system maintains a higher level of security against several types of attackers compared to standard CIR methods.

Positioning with ultrawideband (UWB) is prominent among industrial localization systems, due to its high-range resolution attributes and lower cost. However, one notable challenge with UWB positioning in industrial environments is the prevalent presence of nonline-of-sight (NLOS) components or signals that degrade localization performance drastically. Coupled with this, industrial settings tend to constantly change making NLOS signals challenging to characterize each time these changes occur. Recently, promising approaches have been proposed to identify NLOS components, however their performances are limited to the specific environment where measurements were performed. Their performance cannot be extended to other unknown environments due to the distribution divergence problem, owing to differences in environments captured by the channel impulse response (CIR) waveforms. This therefore requires laborious processes of data collection and training environment-specific models for NLOS identification. In this article, we propose a robust transfer learning-based NLOS identification approach, which harnesses transition information via cross-domain mappings from both source and target domains, to construct representative homogeneous features of both domains. The representative homogeneous features capture discriminative information of both domains, while reducing the distribution divergence between the domains, making it easy to classify LOS and NLOS components from both environments together. To test the robustness of our approach, we perform extensive simulations with CIR data collected from two distinct environments—“hard NLOS” (characterized by high relative permittivity of surrounding objects, e.g., thick concrete walls, metallic objects, etc.) and “soft NLOS” (characterized by low relative permittivity of surrounding objects, e.g., plasterboard walls). Our proposed approach is not just effective in transferring knowledge between distinct environments, but significantly outperforms state-of-the-art works to NLOS identification in UWB positioning networks, while reducing the laborious process of data collection in the target domain.

In the fourth industrial revolution (Industry 4.0), robotics and autonomous navigational systems are essential for smart agriculture. Industrial smart agriculture relies heavily on autonomous navigational systems, which have important uses in unmanned farms, industrial supply chains, etc. For effective navigation of autonomous robotic systems in industrial settings, indoor-based positioning and navigation technologies play key roles. However, positioning performance is severely impacted by the abundance of Non-Line-Of-Sight (NLOS) components due to the dynamic nature of industrial environments. Different approaches have been proposed in literature for identifying and mitigating NLOS components in UWB positioning systems. However, the performance of these proposed approaches on par in multiple distinct environments is unknown. In this paper, we experimentally investigate and compare the performance of recent UWB-based state-of-the-art approaches to NLOS identification and mitigation on par, in distinct and dynamic obstructed settings to ascertain two key insights: i) how the performance of existing approaches change based on the environment type; ii) the impact of the environment type on NLOS identification and mitigation.

Alertness detection is an important component of systems used to detect driver fatigue in order to prevent road accidents. Various approaches have been proposed in literature, including the use of sensors that track physiological markers and camera based systems that rely on computer vision techniques to track facial markers. In this paper, we adopt liveness detection to determine alertness. Liveness detection is a method used in biometrics to determine if a face, or fingerprint, is from a live person. The results show that the approach is robust to different lighting conditions.

Mobile phones are becoming a common tool for people to make the payments. The current peer-to-peer mobile based payment system allows two parties to use physical location-limited interaction between their devices to facilitate secure payment. This physical location-limited interaction is ensured by enabling wireless proximity through Near Field Communication (NFC) technology embedded in mobile phones. However, the NFC technology is vulnerable to relay attacks which is a very challenging security problem. This paper proposes a novel new proximity channel based on vibration for peer-to-peer mobile payment system. The built-in vibrator and accelerometer on the phone are used to send and receive the information. The communication ensures the payment is conducted at a close distance. This paper also compares and analyse the method with the other method such as the phone vibration data and encrypt One Time Password (OTP) as the vibration pattern for payment. The result shows that the proposed method is able retrieve the information successfully from the other smartphones and guarantees the transaction is safe from relay attacks and eavesdropping.

Identifying non-line-of-sight (NLOS) conditions is important to discard, or improve, any location estimates that have been estimated with NLOS ranges. Typically, NLOS identification relies on channel statistics that have been collected for both LOS and NLOS channels. We investigate NLOS identification using distance residuals instead. The results show that distance residuals can be used to identify location estimates with NLOS ranges with very high accuracy, and that in some cases, individual NLOS ranges can also be identified.

It is well known that location accuracy is low in non-line-of-sight (NLOS) scenarios. Several techniques have been proposed to mitigate ranging errors to improve location accuracy. These techniques play an important role in accurate localization for many applications which target safety and productivity in harsh industrial environments. In some cases, these mitigation techniques target specific NLOS scenarios, therefore such scenarios have to identified before mitigation can be applied. In this paper, we study identification of two types of NLOS scenarios that are common indoors: Through-the-Wall (TTW) and Around-the-Corner (ATC). We conduct a measurement campaign in various indoor TTW and ATC scenarios, and show that these two types of NLOS scenarios can be differentiated with high accuracy using channel statistics from ultra-wideband radios.

Accurate ranging and localization in non-line-of-sight (NLOS) conditions is an open research problem. In indoor environments, NLOS causes ranging and location errors due to reflections, refraction, and other propagation phenomena. This article proposes a method to mitigate ranging errors caused by through-the-wall (TTW) NLOS conditions. We develop a TTW ranging model that has less parameters than the conventional ranging model found in the literature and evaluate it using measurements from ultrawideband radios. The developed ranging model expresses the difference between NLOS and line-of-sight (LOS) ranges, i.e., bias, in terms of walls' relative permittivity and thickness. NLOS ranges expressed with the proposed TTW ranging model are used as input to a trilateration algorithm. The proposed method is evaluated via simulations, and it is shown that localization using the simplified ranging model as input to the trilateration algorithm effectively mitigates NLOS ranging errors, resulting in location estimates that are close to LOS location estimates.

This paper describes the design, implementation and test results of a battery-operated wireless airflow sensor for use in mining applications. The sensor uses ultrasonic transducers for flow estimation and the ISA100 standard for wireless communication. The work demonstrates the feasibility of the solution and identifies the remaining work needed to obtain a commercial product.

This paper draws attention to techniques available for the minimization of control overhead in software-defined wireless sensor networks (SDWSNs). Software-defined networking (SDN) promises improved management flexibility and control for inherently resource-constrained and heterogeneous wireless sensor network (WSN) implementations. However, due to the in-band traffic channel available for data and control traffic in SDN-based WSNs, overhead control traffic has been viewed as a bottleneck affecting network performance and controller responsiveness. A discussion on the need for control message quenching (CMQ) and the various categories of CMQ implementations in SDWSN is made in this paper. Furthermore, a CMQ algorithm based on reducing duplicate flow request packets is discussed and demonstrated for implementation in an SDN-based WSN framework. Results show a significant reduction in control overhead traffic and noticeable improvement in energy efficiency. However, trade-offs in terms of packet delivery rate and packet delay are also observed as a result of the CMQ algorithm. A discussion on future work necessary to optimize CMQ algorithms in order to minimize the associated trade-offs is also made.

Accurate indoor positioning is challenging due to non-line-of-sight (NLOS) conditions which cause ranging and location errors. This paper proposes an iterative algorithm to improve location accuracy in NLOS conditions caused by through-the-wall (TTW) propagation. The proposed algorithm uses a floor plan with details of walls' locations and dimensions. The algorithm reduces the NLOS range between a tag and anchors iteratively, resulting in a final location that is closer to the tag's true location than the NLOS estimated location. It is shown that the algorithm can reduce the impact of NLOS conditions on location accuracy significantly.

There is a need for robust positioning systems that can operate in noisy environments such as in hospitals. Although there have been several systems proposed in literature, most systems are aimed at conventional environments such as office buildings or shopping malls. In this paper, a robust ultrasound based positioning system aimed specifically at noisy environments is developed. The system consists of nodes equipped with RF transceivers and ultrasound transducers and estimates the location of mobile tags using time-of-arrival. It is shown that the accuracy attained is better than 35 cm at an update rate of 3 seconds in both line-of-sight and non-line-of-sight conditions.

For a wide range of applications in industry, it is sometimes necessary to perform acoustic source localization. In this paper, a passive sound localization and classification system is designed and implemented. Each sensor consists of a microphone array which is used to detect the direction-of-arrival (DoA) of an acoustic signal. Multiple DoA sensors can be combined to form a wireless sensor network. The system can detect the acoustic signature of power tools and the effectiveness of the system to be used as an early warning system to detect misuse of machinery is demonstrated. It is shown that the system can detect the DoA of an acoustic signal with an overall mean estimation error of 7° and can correctly classify the signal source with a classification rate of 71.5%.

Wireless localization has been the focus of research due to the wide range of applications it can enable, particularly in industrial hazardous areas where warning systems are crucial for safety. Although there are a number of different technologies available for indoor localization such as Wi-Fi and ultra-wideband, Bluetooth based localization is usually less expensive to deploy and all smartphones have the ability to receive Bluetooth signals. In this paper, a Bluetooth Low Energy (BLE) location system is proposed. The system consists of a number of beacons that serve as fixed references and a smartphone that serves as a mobile tag. Results show that the system can locate a mobile tag (i.e. smartphone) with an average location error of 1.8 m at an update rate higher than 0.5 seconds.

Localization is important for a wide range of industries and applications. In underground mining, for instance, it is helpful to know the miners' locations, particularly in emergency situations. One way this can be achieved is by using ultrasonic based localization. This paper presents the design and implementation of a wireless sensor network which can be deployed in underground mines to perform time-difference-of-arrival based localization. It is shown that the implemented ultrasound receivers are resistant to noisy conditions that may arise in harsh underground environments.

South Africa could potentially face a shortage of water in the near future. Efficient and low cost methods to determine water usage are vital to help prevent this issue. Flow and usage meters are necessary to ensure accurate usage readings. An electromagnetic flow meter and a water usage meter were developed. The designed module can be implemented on a standard water pipe at residential areas. The developed system harvests energy using a solar panel.

Conventional fire detection systems have a tendency of being triggered by false positives. In this paper, we discuss the design and implementation of a smart fire detection system using a Wireless Sensor Network (WSN) and Global System for Mobile (GSM) communication to detect fires effectively and reduce false positives. The proposed system uses smoke and temperature sensors. SMS capability via GSM was implemented so that occupants can interact with the fire detection system and aid in the detection of false positives. The aim of this work was to design and implement a fire detection system that detects fires effectively and reduces false positives. The results show that the system meets the specifications.

This paper describes the work that was carried out in designing a public addressing system based on Wireless Sensor Networks (WSN). The system uses a VS1053 codec to perform all the required encoding and decoding, and an STM32W108CC as a controller, with the capability of performing wireless communication. Satisfactory results were obtained from the public address system. The playback had an average Mean Opinion Score (MOS) of 4.0. The average data transfer rate was maintained over a distance of 20 m.

Monitoring systems are necessary in buildings to monitor the working environment. This paper describes the development of a wireless monitoring system which can be deployed in a building. The system measures carbon dioxide, carbon monoxide and temperature. The system developed in this paper can serve as the monitoring component of a HVAC control system and function as an indoor air quality monitor independently.

Accurate indoor localization requires non line-of-sight ranging error identification and mitigation. Current research has focused on methods that improve accuracy but are too complex to be executed in resource-constrained hardware in real-time. In this paper, we propose and evaluate a non line-of-sight mitigation technique using impulse radio ultra-wideband (IR-UWB) experimental ranging data. We show that using this technique, ranging non-line-of-sight (NLOS) errors can be significantly reduced in the location estimate. The method is less complex than other methods used in related work and can potentially be implemented on microcontrollers.

Many vehicle accidents are caused by driver fatigue. Systems to monitor driver fatigue can contribute to a decrease in fatalities. This paper describes the development of a multi-sensor system for driver fatigue detection. The system achieves this by monitoring eye closure and wheel steering movements, and is able to alert the driver of any detected anomalies. Various techniques are suggested for registering the location coordinates. If it is detected that the driver is falling asleep, the system alerts the driver through audible and visual cues and sends an SMS to a third party reporting the occurrence.

In this paper, an indoor office locator system is developed. The product developed uses body sensors to detect incoming objects using indoor positioning tracking algorithm which run on a server application to guide the user in an office environment were designed and developed. It is shown that overall the final system allowed a partially blind user to navigate the office with relative safety and accuracy.

Biometric systems are important for access control and authentication in various application scenarios. Single biometrics can be selected for authentication, but a multimodal approach is typically more reliable. In this paper, a multimodal biometric authentication system is developed. It consists of wireless sensor nodes equipped with accelerometers and infrared cameras, which enable analysis of gait and vein scanning for authentication. Observed error equal rates for the gait and vein authentication are 13% and 11% respectively, whilst the equal error rate for the combined metrics is 8%.

Electric shocks due to high voltage lines can pose serious health risks to workers. Reliable and efficient systems to alert workers of nearby live power lines are necessary. In this paper, a personal high voltage safety system with wear monitoring is designed and implemented. A wrist module which consists of an electric field detector and optical heart rate monitor is developed from first principles. The complete system allows the heart rate of a subject to be monitored and reported wirelessly to a GSM/GPS enabled module placed on a vehicle. The system can operate reliably in an area with high electromagnetic fields.

In emergency situations such as fires in homes and offices, it is often the case where members of a response team (eg. firefighters) are not able to locate each other due to fire and smoke. It is desirable to have a system which is able to locate all personnel such that a team leader can monitor their location and to enable the firefighters themselves to know their proximity to other firefighters. This paper discusses the design and implementation of an impulse-radio ultra-wideband sensor network that can be easily deployed around the perimeter of a building and can be used to locate personnel indoors. It is found that the ranging accuracy of the sensor network meets the accuracy requirements but has limited range, especially through very thick walls.

Hazardous environments at the workplace are a significant contributor to injuries due to accidents as well as chronic diseases. There are many occupational health and safety (OHS) systems, but they are costly or not flexible. This paper presents a low-cost OHS. It consists of various sensors that can be used to monitor whether a safety helmet is being worn, the worker is mobile and safety boots are being worn. The system interfaces with a wireless sensor network and is suitable for operation in environments such as underground mines and sawmills.

Impulse radio ultrawideband ranging has recently received significant attention due to the high accuracy it can achieve. Although most research efforts have focused on ranging in indoor and outdoor environments, other environments such as harsh industrial environments introduce unique challenges. This paper discusses the impact of propagation characteristics of harsh industrial environments on ranging accuracy, and also discusses principles and challenges of non-line-of-sight identification in industrial scenarios. To illustrate these challenges, a measurement campaign using 802.15.4a radios was conducted in a Heavy Machines Laboratory. The results show that the non-line-of-sight condition can be accurately identified if adequate models for such an environment are used.

Recently, there has been significant research focus on smart cities and how to use resources efficiently. Parking space, in particular, is scarce in most metropolitan areas and intelligent systems are required to coordinate parking. This paper presents a wireless system for locating parking spots remotely via a smartphone, and a wireless sensor node which determines if parking spots are vacant or not. It is found that the system is highly efficient and has high accuracy, even at long ranges.

Impulse radio ultra-wideband (IR-UWB) ranging and localization have recently received significant attention due to the high accuracy and precision. This high accuracy can be exploited for many location aware applications in a wide variety of environments. Although most research efforts have focused on location-aware applications for indoor or outdoor environments, there are other environments, such as industrial, which introduce unique challenges. In an effort to understand how industrial environments affect IR-UWB based ranging and localization performance, this paper introduces the principles behind ranging in industrial environments and highlights practical challenges which have an impact on the ranging accuracy of IR-UWB. Results from field tests which illustrate the impact of harsh conditions on the ranging accuracy are presented.

Wireless underground sensor networks (WUSNs) are a category of wireless sensor networks (WSNs) with buried nodes, which communicate wirelessly through soil with sensor nodes located aboveground. As the communication medium (i.e., soil) between traditional over-the-air WSNs and WUSNs differs, communication characteristics have to be fully characterized for WUSNs, specifically to enable development of efficient communication protocols. Characterization of link quality is a fundamental building block for various communication protocols. The aim of this paper is to experimentally investigate the link quality characteristics of the three communication channels available in WUSNs for underground pipeline monitoring to gain further insight into protocol development for WUSNs. To this end, received signal strength (RSS), link quality indicator (LQI), and packet reception ratio (PRR) are characterized for the three communication channels in WUSNs. The RSS and PRR results show that the underground-to-underground channel is highly symmetric and temporally stable, but its range is severely limited, and that the aboveground-to-underground/underground-to-underground channels are asymmetric and exhibit similar temporal properties to over-the-air communication channels. Interestingly, the results show that RSS is a better indicator of PRR than LQI for all three channels under consideration.

In various industrial automation applications, positioning enables location awareness which can be exploited in applications such as robotic precision control, amongst others. This paper discusses positioning for industrial automation applications. Examples of applications from an infrastructure perspective are presented, and the integration of high precision positioning technology into existing network infrastructure for such applications is discussed, as well as challenges involved. An impulse-radio ultra-wideband 802.15.4a based system for high accuracy/precision positioning is presented, which shows promising results, therefore motivating the use of UWB as a high accuracy and precision technology for positioning applications in future industrial automation systems.