Nowadays, and more than a decade after the first steps towards autonomous driving, we keep heading to achieve fully autonomous vehicles on our roads, with LiDAR sensors being a key instrument for the success of this technology. Such advances trigger the emergence of new players in the automotive industry, and along with car manufacturers, this sector represents a multibillion-dollar market where everyone wants to take a share. To understand recent advances and technologies behind LiDAR, this article presents a survey on LiDAR sensors for the automotive industry. With this work, we show the measurement principles and imaging techniques currently being used, going through a review of commercial systems and development solutions available in the market today. Furthermore, we highlight the current and future challenges, providing insights on how both research and industry can step towards better LiDAR solutions.

Over the last few years, the gap between FPGA and ASIC performance levels have been narrowed due to the constant development of FPGA technology. The high performance, together with lower development costs and a shorter time-to-market, turns FPGA based platforms attractive for a huge range of applications, among them, Time-to-Digital Converters (TDCs). It is therefore important to analyse the evolution of FPGA-based TDCs, to better understand where the research efforts should be focused in the near future. This work presents and discusses the improvements on the FPGA-based TDC research, aiming to be a starting point for new studies on this field, with some guidelines for future research. A state-of-the-art literature review on FPGA-based TDC is presented, aiming to categorize and discuss the existing architectures. This discussion addresses architectures characteristics, limitations and areas of application.

With the advent of the Internet of Things (IoT), security has emerged as a major design goal for smart connected devices. This explosion in connectivity created a larger attack surface area. Software-based approaches have been applied for security purposes; however, these methods must be extended with security-oriented technologies that promote hardware as the root of trust. The ARM TrustZone can enable trusted execution environments (TEEs), but existing solutions disregard real-time needs. Here, the authors demonstrate why TrustZone is becoming a reference technology for securing IoT edge devices, and how enhanced TEEs can help meet industrial IoT applications real-time requirements.

The number of devices connected to the Internet is increasing, exchanging large amounts of data, and turning the Internet into the 21st-century silk road for data. This road has taken machine learning to new areas of applications. However, machine learning models are not yet seen as complex systems that must run in powerful computers (i.e., Cloud). As technology, techniques, and algorithms advance, these models are implemented into more computational constrained devices. The following paper presents a study about the optimizations, algorithms, and platforms used to implement such models into the network’s end, where highly resource-scarce microcontroller units (MCUs) are found. The paper aims to provide guidelines, taxonomies, concepts, and future directions to help decentralize the network’s intelligence.

Wireless Sensor Networks are an emerging technology which has been recently adopted in many applications. Due to its wireless nature, the analysis of the radio propagation models plays an important role for performance evaluation in both theoretical and practical aspects. In this regards, path loss exponent is one of the most important parameter which has been considered widely in wireless communications analysis. There are several theoretical evaluations of path loss exponent for wireless sensor networks available in the literature. However there is a lack of experimental evaluation of both path loss exponent and the effect of shadowing. In this paper, three environments (free space, in building and industrial), where wireless sensor nodes are widely deployed, have been chosen in order to evaluate the experimental analysis. Path loss and path loss exponent are measured by means of Received Signal Strength Indicator (RSSI) and based on them, the standard deviation of shadowing effect is also calculated. All the measured parameters are compared with the theoretical analysis available in the literatures.

In a world with an accelerated population aging, there is an increasingly interest in developing solutions for the elderly living assistance. The Internet of Things is a new reality that is completely changing our everyday life, and promises to revolutionize modern healthcare by enabling a more personalized, preventive and collaborative form of care. Aiming to combine these two important topics, this work presents an IoT-ready solution for the elderly living assistance which is able to monitor and register patients vital information as well as to provide mechanisms to trigger alarms in emergency situations. Its effective low-power/low-cost and wireless characteristics turns this solution suitable to be used anywhere and by anyone, in a discrete and comfortable wristband. Experiments demonstrated a good system performance for the implemented functionalities, and regarding the autonomy we obtained an average battery lifetime of 306 hours (around 12 days). For the working range, the system have proved to perform well within a range of 60 meters before the out-of-range warning being triggered.