This study evaluates the maximum theoretical exposure to radiofrequency (RF) electromag- netic fields (EMFs) from a Fifth-generation (5G) New Radio (NR) base station (BS) while using four commonly used mobile applications: YouTube for video streaming, WhatsApp for voice calls, Instagram for posting pictures and videos, and running a Video game. Three factors that might affect exposure, i.e., distance of the measurement positions from the BS, measurement time, and induced traffic, were examined. Exposure was assessed through both instantaneous and time-averaged extrapolated field strengths using the Maximum Power Extrapolation (MPE) method. The former was calculated for every measured SS-RSRP (Secondary Synchronization Reference Signal Received Power) power sample obtained with a sampling resolution of 1 second, whereas the latter was obtained using a 1-min moving average applied on the applications’ instantaneous extrapolated field strengths datasets. Regarding distance, two measurement positions (MPs) were selected: MP1 at 56 meters and MP2 at 170 meters. Next, considering the measurement time, all mobile application tests were initially set to run for 30 minutes at both MPs, whereas the video streaming test (YouTube) was run for an additional 150 minutes to investigate the temporal evolution of field strengths. Considering the traffic, throughput data vs. both instantaneous and time-averaged extrapolated field strengths were observed for all four mobile applications. In addition, at MP1, a 30-minute test without a User Equipment (UE) device was conducted to analyze exposure levels in the absence of induced traffic. The findings indicated that the estimated field strengths for mobile applications varied. It was observed that distance and time had a more significant impact than the volume of data traffic generated (throughput). Notably, the exposure levels in all tests were considerably lower than the public exposure thresholds set by the ICNIRP guidelines.INDEX TERMS 5G NR, C-band, human exposure assessment, mobile applications, traffic data, maximum extrapolation method, RF-EMF.
MULTIFILE
The SynergyS project aims to develop and assess a smart control system for multi-commodity energy systems (SMCES). The consortium, including a broad range of partners from different sectors, believes a SMCES is better able to incorporate new energy sources in the energy system. The partners are Hanze, TU Delft, University of Groningen, TNO, D4, Groningen Seaports, Emerson, Gain Automation Technology, Energy21, and Enshore. The project is supported by a Energy Innovation NL (topsector energie) subsidy by the Ministry of Economic Affairs.Groningen Seaports (Eemshaven, Chemical Park Delfzijl) and Leeuwarden are used as case studies for respectively an industrial and residential cluster. Using a market-based approach new local energy markets have been developed complementing the existing national wholesale markets. Agents exchange energy using optimized bidding strategies, resulting in better utilization of the assets in their portfolio. Using a combination of digital twins and physical assets from two field labs (ENTRANCE, The Green Village) performance of the SMCES is assessed. In this talk the smart multi-commodity energy system is presented, as well as some first results of the assessment. Finally an outlook is given how the market-based approach can benefit the development of energy hubs.
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