As Vehicle-to-Everything (V2X) communication technologies gain prominence, ensuring human safety from radiofrequency (RF) electromagnetic fields (EMF) becomes paramount. This study critically examines human RF exposure in the context of ITS-5.9 GHz V2X connectivity, employing a combination of numerical dosimetry simulations and targeted experimental measurements. The focus extends across Road-Side Units (RSUs), On-Board Units (OBUs), and, notably, the advanced vehicular technologies within a Tesla Model S, which includes Bluetooth, Long Term Evolution (LTE) modules, and millimeter-wave (mmWave) radar systems. Key findings indicate that RF exposure levels for RSUs and OBUs, as well as from Tesla’s integrated technologies, consistently remain below the International Commission on Non-Ionizing Radiation Protection (ICNIRP) exposure guidelines by a significant margin. Specifically, the maximum exposure level around RSUs was observed to be 10 times lower than ICNIRP reference level, and Tesla’s mmWave radar exposure did not exceed 0.29 W/m2, well below the threshold of 10 W/m2 set for the general public. This comprehensive analysis not only corroborates the effectiveness of numerical dosimetry in accurately predicting RF exposure but also underscores the compliance of current V2X communication technologies with exposure guidelines, thereby facilitating the protective advancement of intelligent transportation systems against potential health risks.
MULTIFILE
In this presented study, we measured in situ the uplink duty cycles of a smartphone for 5G NR and 4G LTE for a total of six use cases covering voice, video, and data applications. The duty cycles were assessed at ten positions near a 4G and 5G base-station site in Belgium. For Twitch, VoLTE, and WhatsApp, the duty cycles ranged between 4% and 22% in time, both for 4G and 5G. For 5G NR, these duty cycles resulted in a higher UL-allotted time due to time division duplexing at the 3.7 GHz frequency band. Ping showed median duty cycles of 2% for 5G NR and 50% for 4G LTE. FTP upload and iPerf resulted in duty cycles close to 100%.
MULTIFILE
Creating and testing the first Brand Segmentation Model in Augmented Reality using Microsoft Hololens. Sanoma together with SAMR launched an online brand segmentation tool based on large scale research, The brand model uses several brand values divided over three axes. However they cannot be displayed clearly in a 2D model. The space of BSR Quality Planner can be seen as a 3-dimensional meaningful space that is defined by the terms used to typify the brands. The third axis concerns a behaviour-based dimension: from ‘quirky behaviour’ to ‘standardadjusted behaviour’ (respectful, tolerant, solidarity). ‘Virtual/augmented reality’ does make it possible to clearly display (and experience) 3D. The Academy for Digital Entertainment (ADE) of Breda University of Applied Sciences has created the BSR Quality Planner in Virtual Reality – as a hologram. It’s the world’s first segmentation model in AR. Breda University of Applied Sciences (professorship Digital Media Concepts) has deployed hologram technology in order to use and demonstrate the planning tool in 3D. The Microsoft HoloLens can be used to experience the model in 3D while the user still sees the actual surroundings (unlike VR, with AR the space in which the user is active remains visible). The HoloLens is wireless, so the user can easily walk around the hologram. The device is operated using finger gestures, eye movements or voice commands. On a computer screen, other people who are present can watch along with the user. Research showed the added value of the AR model.Partners:Sanoma MediaMarketResponse (SAMR)
Management policy for protected species is currently often based on literature reviews and expert judgement, even though it requires tailor-made species knowledge on a local level. While wildlife management should preferably be evidence based, tailor-made field data is seldom used in current practices, because it is hardly available, difficult to collect and expensive. Recent development of digital technology is changing the field of wildlife management with “more, better, faster and cheaper” ways of data collection. Especially automated collection of field data with different types of sensors is promising, whereas miniaturization and low cost mass-production increase availability and use of these sensors. For collection of field data about predator-prey interactions, there is a need to develop wireless sensor networks that automatically identify different species in a community, while they record their spatially explicit data and their behaviour. Therefore, we will put together a consortium of partners that will develop a EU LIFE programme proposal, with the focus to develop a sensor network necessary to automatically monitor multiple species (i.e., species communities) for species conservation management. The consortium will consist of Van Hall Larenstein, Sovon Dutch Centre for Field Ornithology, the Dutch Mammal Society, Sensing Clues and DIKW intelligence. It will bring together a strong mix of expert knowledge on applied species conservation and wildlife management, ecological field research, wildlife intelligence, and handling and analysis of big data. This project matches the Top sector High-tech Systems & Materials, and revolves around 4 distinct phases: selection of potential consortium partners, exploration of the problem, working towards a common action perspective and writing a EU LIFE programme proposal. We will use knowledge co-creation techniques to explore the first three project phases.
Internet of Things (IoT) is tagging low power devices, miniaturized, with machine-readable identification tags, which are integrated with sensors to collect information and wireless technology to connect them with the Internet. These devices have a very low energy usage. Powering these devices with battery is very labor intensive, costly and tedious especially as number of nodes increases, which is in many applications, is the case. Hence the main objective of this proposal is to introduce new product called RF Colletor, in the market such that IoT devices function independent of battery. Using the suggested approach the wille be energized using Radio Frequency (RF) energy harvesting. RF Collector wirelessly capture the RF energy that is wasted in space, and re-use it again as the power source for IoT devices and hence making them autonomous of battery. The ability to harvest RF energy enables wireless charging of low-power devices in real time. This has resulting benefits to sustainability, cost reduction, product design, usability, and reliability.
