5,219 research outputs found
Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)
Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft
RFID Localisation For Internet Of Things Smart Homes: A Survey
The Internet of Things (IoT) enables numerous business opportunities in
fields as diverse as e-health, smart cities, smart homes, among many others.
The IoT incorporates multiple long-range, short-range, and personal area
wireless networks and technologies into the designs of IoT applications.
Localisation in indoor positioning systems plays an important role in the IoT.
Location Based IoT applications range from tracking objects and people in
real-time, assets management, agriculture, assisted monitoring technologies for
healthcare, and smart homes, to name a few. Radio Frequency based systems for
indoor positioning such as Radio Frequency Identification (RFID) is a key
enabler technology for the IoT due to its costeffective, high readability
rates, automatic identification and, importantly, its energy efficiency
characteristic. This paper reviews the state-of-the-art RFID technologies in
IoT Smart Homes applications. It presents several comparable studies of RFID
based projects in smart homes and discusses the applications, techniques,
algorithms, and challenges of adopting RFID technologies in IoT smart home
systems.Comment: 18 pages, 2 figures, 3 table
Quality assessment technique for ubiquitous software and middleware
The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future
Telemedicine
Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios
Adaptations and Analysis of the AFIT Noise Radar Network for Indoor Navigation
After several years of development, the AFIT Noise Radar Network (NoNET) has proven to be an extremely versatile system for many standard radar functions. This pallet of capabilities includes through the wall target tracking capabilities due to its wide bandwidth and UHF operations. Utilizing White Gaussian Noise as its waveform, the NoNET can operate at much lower power levels than other comparable systems while remaining extremely covert. In an effort to explore new applications, the question arose could the NoNET provide a viable option for navigation capability in GPS denied and indoor environments? This research aims to provide proof of concept and demonstration of the navigation function execution with the NoNET in indoor, multipath-ridden environments. Results demonstrate that the NoNET is currently capable of locating a receiver to accuracies of approximately 1 foot. Multipath, background RF interference, and network timing were investigated and solutions to mitigate the limitations imposed by each were developed with the potential to significantly improve accuracy. Future upgrades to the current NoNET hardware package were also investigated in order to provide a near real-time, portable solution to navigation in GPS denied environments
Edge Artificial Intelligence for Real-Time Target Monitoring
The key enabling technology for the exponentially growing cellular communications sector is location-based services. The need for location-aware services has increased along with the number of wireless and mobile devices. Estimation problems, and particularly parameter estimation, have drawn a lot of interest because of its relevance and engineers' ongoing need for higher performance. As applications expanded, a lot of interest was generated in the accurate assessment of temporal and spatial properties.
In the thesis, two different approaches to subject monitoring are thoroughly addressed. For military applications, medical tracking, industrial workers, and providing location-based services to the mobile user community, which is always growing, this kind of activity is crucial.
In-depth consideration is given to the viability of applying the Angle of Arrival (AoA) and Receiver Signal Strength Indication (RSSI) localization algorithms in real-world situations. We presented two prospective systems, discussed them, and presented specific assessments and tests. These systems were put to the test in diverse contexts (e.g., indoor, outdoor, in water...). The findings showed the localization capability, but because of the low-cost antenna we employed, this method is only practical up to a distance of roughly 150 meters. Consequently, depending on the use-case, this method may or may not be advantageous. An estimation algorithm that enhances the performance of the AoA technique was implemented on an edge device.
Another approach was also considered. Radar sensors have shown to be durable in inclement weather and bad lighting conditions. Frequency Modulated Continuous Wave (FMCW) radars are the most frequently employed among the several sorts of radar technologies for these kinds of applications. Actually, this is because they are low-cost and can simultaneously provide range and Doppler data. In comparison to pulse and Ultra Wide Band (UWB) radar sensors, they also need a lower sample rate and a lower peak to average ratio. The system employs a cutting-edge surveillance method based on widely available FMCW radar technology. The data processing approach is built on an ad hoc-chain of different blocks that transforms data, extract features, and make a classification decision before cancelling clutters and leakage using a frame subtraction technique, applying DL algorithms to Range-Doppler (RD) maps, and adding a peak to cluster assignment step before tracking targets. In conclusion, the FMCW radar and DL technique for the RD maps performed well together for indoor use-cases. The aforementioned tests used an edge device and Infineon Technologies' Position2Go FMCW radar tool-set
Effect of Cyber Vulnerabilities on the Adoption of Self-Driving Vehicles – A Review
One of the leading disruptive technologies in the upcoming technological revolution is Self-Driving vehicles. However, the absence of security is the greatest obstacle to adoption. This study looks at how cybersecurity impacts the adoption of driverless cars. The purpose of this paper is to perform a literature review supporting the in-depth analysis of cybersecurity and its impacts on the slower adoption rate of Self-Driving Vehicles. The study\u27s primary goal is to determine the connection between worries about cybersecurity and the rate of adoption of self-driving vehicles. Driverless vehicles are the most effective and cutting-edge technology in the transportation sector, yet there are barriers to their widespread adoption because of cybersecurity worries. As a result, this study will clarify the cybersecurity issues that contributed to the slower deployment of autonomous vehicles. The NIST Cybersecurity Framework serves as the study\u27s theoretical foundation. This paradigm consistently identifies the barriers to new technology adoption in cybersecurity
Radicalization of Airspace Security: Prospects and Botheration of Drone Defense System Technology
The development of a comprehensive and decisive drone defense integrated control system that can provide maximum security is crucial for maintaining territorial integrity and accelerating smart aerial mobility to sustain the emerging drone transportation system (DTS) for priority-based logistics and mobile communication. This study explores recent developments in the design of robust drone defense control systems that can observe and respond not only to drone attacks inside and outside a facility but also to equipment data such as CCTV security control on the ground and security sensors in the facility at a glance. Also, it considered DDS strategies, schema, and innovative security setups in different regions. Finally, open research issues in DDs designs are discussed, and useful recommendations are provided. Effective means for drone source authentication, delivery package verification, operator authorization, and dynamic scenario-specific engagement are solicited for comprehensive DDS design for maximum security
Received: 2023-03-07
Revised: 2023-04-2
Multiple Person Localization Based on Their Vital Sign Detection Using UWB Sensor
In the past period, great efforts have been made to develop methods for through an obstacle detection of human vital signs such as breathing or heart beating. For that purpose, ultra-wideband (UWB) radars operating in the frequency band DC-5 GHz can be used as a proper tool. The basic principle of respiratory motion detection consists in the identification of radar signal components possessing a significant power in the frequency band 0.2–0.7 Hz (frequency band of human respiratory rate) corresponding to a constant bistatic range between the target and radar. To tackle the task of detecting respiratory motion, a variety of methods have been developed. However, the problem of person localization based on his or her respiratory motion detection has not been studied deeply. In order to fill this gap, an approach for multiple person localization based on the detection of their respiratory motion will be introduced in this chapter
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