GPS Capability in Power Sensitive ITS Applications

Road traffic, by dimensions, weights and speeds of vehicles which is moving is a danger that requires precise deployment rules, advanced technical systems for safe movement, an appropriate infrastructure etc. Road safety is an issue of interest to all citizens, each of which can contribute to improving safety on public roads. Although the measures taken in this area have proven, road accidents remain unacceptably high. One of the main causes of serious accidents is the failure of its speed and road weather conditions. For this reason in this paper we present an electronic road traffic information and monitoring system. The system consists of a traffic information system and detection equipment and weather monitoring, video imaging to speeding vehicles and the weight permitted for movement on public roads.

A widely-tunable and power-scalable clock generator for ultra-low power (ULP) applications is presented. Benefitting from a novel self-adjustable loop frequency response, the proposed phase-locked loop based clock generator exhibits a tuning range of three decades. Implemented in 0.13 µm CMOS, the circuit occupies 0.06 mm2, while its power dissipation is 9 pW/Hz, proportional to the output clock frequency with 350 nW stand-by power. The circuit remains stable with scalable dynamics for frequency steps (upward and downward) as large as a factor of ×1024. The presented clock generator has been designed to be compatible with subthreshold source-coupled logic (STSCL) topology that can be used for ultra-low power applications such as in bio-medical systems.

The increasing demand in electronic portability imposes low power consumption as a key metric to analog and digital circuit design. Tunnel FET (TFET) devices have been explored mostly in digital circuits, showing promising results for ultra-low power and energy efficient circuit applications. The TFET presents a low inverse sub-threshold slope (SS) that allows a low leakage energy consumption, desirable in many digital circuits, especially memories.In this book, the TFET is explored as an alternative technology also for ultra-low power and voltage conversion and management circuits, suitable for weak energy harvesting (EH) sources. The TFET distinct electrical characteristics under reverse bias conditions require changes in conventional circuit topologies. In this book, ultra-low input power conversion circuits based on TFETs are designed and analyzed, evaluating their performance as rectifiers, charge pumps and power management circuits (PMC) for RF and DC EH sources.

Air deterioration and high toxicity affects life quality and longevity. Most important is pollution and toxicity impact upon health and disease management. Air born sicknesses and health problems are a permanent challenge for air dependent life-forms. Lately have been recorded manifestations and a complex phenomenology of air partially transferred pathogenic agents. The air quality is subject to investigation in order to provide a better management of the pollution control system. Pollution is a major contributor to air quality deterioration and to health problem multiplication. Present day pandemic is thought to be partially transmitted through air and by direct contact. Low air quality may be a serious contributing factor to sickness promotion. Air pollution due to road traffic and livestock is one such factor. The main objective of the paper is to investigate some important failures and vulnerabilities recorded in the road traffic air quality monitoring system during 2020 pandemics in our country and in Cluj. Thus, the evolution of chemical composition has been put under the spot of scientific investigation. Failures and weak points have been acknowledged and considered for improvement. At least twelve significant system failures and multiple vulnerabilities have been recorded due to sensor faults and unit malfunction. Social lockdown reduced all pollutants, but some units failed to indicate it properly.

Specific class of applications having moderate throughput and low power budget puts pressing need on ultralow energy level operation of device instead of higher performance. Ultralow energy operation is possible only in subthreshold region and is attractive for hand held devices. However, operating Si-MOSFETs in subthreshold region to achieve low power faces variability and reduced performance problems. Therefore, it is important to investigate the possibility of extending the use of most promising nano device Carbon Nano Tube Field Effect Transistor (CNFET) even for ultra low power (ULP) applications. As SRAM is an important block used in many electronics application therefore this paper investigates CNFET based SRAM for achieving ultralow energy level with better performance. It has been found that the optimized CNFET based cell shows 39% improvement in read SNM, also consume very less leakage power and outperforms in all design features as compared to Si-MOSFET cell.

Recently, various ultra-low power applications such as Internet-of-Things (IoT), wearable devices, biomedical devices, AI, and machine learning have emerged opening up a new domain of integrated circuits design. In these applications, ultra-low voltage circuit techniques for improving the power and energy efficiencies have been the main research focus. One of the most challenging functional blocks in ultra-low power systems is memory where SRAMs are dominantly employed. Since SRAMs occupy majority of the power in those systems, design of ultra-low power SRAMs is a critical task for power and energy efficiencies. In addition, SRAMs have started to be employed in realizing Physically Unclonable Function (PUF) and Computation-in-Memory (CIM). Even though basic SRAM design methodologies can be adopted in these applications, several additional design challenges need to be carefully addressed. This tutorial will present the basics in ultra-low power SRAMs followed by state-of-the-art ultra-low power SRAM design techniques. Design challenges and several methodologies for SRAM-based PUFs and SRAM-based CIM will also be explained. Finally, I will discuss future directions in ultra-low power SRAMs including various emerging nonvolatile memory devices such as STTRAM, RRAM, etc.

Ultra-low power systems require very low standby power and operate at moderate speeds. Traditionally, the normal surface channel inversion (SCI) FET would be considered better for such applications when compared to the buried channel (BC) FET, since the BC FET has always shown more short channel effects in past research. However, past comparisons between the two FETs have been done with the highest frequency in mind and the same conclusion need not hold true for moderate speed, ultra-low power applications. Due to a better subthreshold slope and negligible band to band tunneling leakage at the drain-halo and drain-channel region, the BC FET is better suited for such applications.

International audience

Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

The automotive and railway industries are rapidly transforming with a strong drive toward automation and digitalization, with the goal of increased convenience, safety, efficiency, and sustainability. Since assisted and fully automated automotive and train transport services increasingly rely on vehicle-to-everything communications and high-accuracy real-time positioning, it is necessary to continuously maintain high-accuracy localization, even in occlusion scenes such as tunnels, urban canyons, or areas covered by dense foliage. In this article, we review the 5G positioning framework of the 3rd Generation Partnership Project in terms of methods and architecture and propose enhancements to meet the stringent requirements imposed by the transport industry. In particular, we highlight the benefit of fusing cellular and sensor measurements, and discuss required architecture and protocol support for achieving this at the network side. We also propose a positioning framework to fuse cellular network measurements with measurements by onboard sensors. We illustrate the viability of the proposed fusion-based positioning approach using a numerical example.

This investigation introduces a new charge controller for GPS trackers, with the objective of offering long-lasting and efficient tracking solutions. The article emphasizes the widespread use of GPS trackers in various sectors, as well as the critical need for sustainable power sources to maintain their effectiveness. The charge controller ensures optimal performance and durability by meticulously choosing components. Experimental investigations confirm the efficacy of the charge controller to deliver a steady power supply to the GPS tracker. The integration of GPS technology with solar PV charging allows for continuous monitoring. The results show that the solar photovoltaic (PV) system reached a peak output voltage of 10 V, ensuring that the battery remained at a stable level of 12.4 V and continually providing the GPS tracker with a steady 5 V. These findings validate the system's capacity to deliver dependable and enduring electricity, signifying notable progress in remote monitoring, asset tracking, and fleet management.

Many applications in the area of location-based services and personal navigation require nowadays the location determination of a user not only in an outdoor environment but also an indoor. Typical applications of location-based services (LBS) mainly in outdoor environments are fleet management, travel aids, location identification, emergency services and vehicle navigation. LBS applications can be further extended if reliable and reasonably accurate three-dimensional positional information of a mobile device can be determined seamlessly in both indoor and outdoor environments. Current geolocation methods for LBS may be classified as GNSS-based, cellular network-based or their combinations. GNSS-based methods rely very much on the satellite visibility and the receiver-satellite geometry. This can be very problematic in dense high-rise urban environments and when transferring to an indoor environment. Especially, in cities with many high-rise buildings, the urban canyon will greatly affect the reception of the GNSS signals. Moreover, positioning in the indoor/outdoor transition areas would experience signal quality and signal reception problems, if GNSS systems alone are employed. The authors have proposed the integration of GNSS with wireless positioning techniques such as WiFi and UWB. In the case of WiFi positioning, the so-called fingerprinting method based on WiFi signal strength observations is usually employed. In this article, the underlying technology is briefly reviewed, followed by an investigation of two WiFi-positioning systems. Testing of the system is performed in two localisation test beds, one at the Vienna University of Technology and another one at the Hong Kong Polytechnic University. The first test showed that the trajectory of a moving user could be obtained with a standard deviation of about ±3–5 m. The main disadvantage of WiFi fingerprinting, however, is the required time consuming and costly signal strength system calibration in the beginning. Therefore, the authors have investigated if the measured signal strength values can be converted to the corresponding range to the access point. A new approach for this conversion is presented and analysed in typical test scenarios.

Indoor energy harvesting using small photovoltaic (PV) cells is still not widely exploited. It can be a solution to supply ultra-low power (ULP) devices for Internet of Things (IoT) applications. However, a PV cell may suffer shading caused by walls, furniture, and human movements. This requires an efficient conversion system that can adapt to voltage variations, demanding a specific adjustable DC-DC converter. The present work aims to propose a fully integrated conversion system for indoor photovoltaic energy harvesting capable to provide a range of voltage conversion ratios (VCRs) suitable for ULP and ultra-low voltage (ULV) applications. The proposed converter is based on a reconfigurable switched-capacitor (SC) topology. A systematic simulation-based methodology for designing the DC-DC converter is presented, including switches and capacitors sizing and operating frequency optimization. Results show that the proposed circuit can obtain 19 different VCRs with an estimated peak efficiency of 94.26%. This is an important step towards a practical self-powered indoor system for IoT applications.

Preface of special issue on explainable AI-empowered Internet of Things for indoor navigation using WIFI sensing

The objective of the article is to describe application of computer vision and artificial intelligence technologies for solving the problems of road infrastructure design.The article evaluates the traditional methods of quantitative and qualitative analysis of traffic flows in terms of labour intensity and accuracy using the method of comparative analysis, the advantages and disadvantages of the considered methods are indicated. A new method of traffic flow analysis using unmanned aerial vehicles and computer vision technology based on convolutional neural networks is proposed. The considered method makes it possible to fully automate collection and analysis of data on traffic flows. The article describes the first application of the proposed method when performing transport and economic surveys within the framework of the design of «Northern bypass of the city of Perm». The advantages of the applied method in relation to the traditional ones are described. To implement this project, software was developed for analysing traffic flows using video materials.Further, traffic monitoring is considered, its goals and objectives are described, the necessary functionality of the road traffic monitoring automation system is indicated, the traffic parameters that it should determine are listed. The methodology for implementation of an automated traffic monitoring system based on video materials on a section of the road is considered.A presented project of a traffic monitoring system makes it possible to extend the previously considered approach to the entire road network. Technologies are described that make it possible to implement this system based on video analytics of materials from CCTV cameras. A method for vehicle re-identification is proposed, and the implementation of this method is demonstrated. The method allows building a correspondence matrix of vehicles recorded by CCTV cameras located on different segments of the road network, as well as determining all traffic parameters for the entire street and road network.The conclusions outline the prospects for development of the developed software in terms of application in intelligent transport systems.