A wearable system/device capable to track key COVID-19 symptoms is presented. Off-the-shelf hardware and software components as simple sensors, general purpose microcontroller, and gadget like mobile devices and peripheries are used to detect and monitor body temperature, heart rate, respiration rate and other vital signs, which are important to alert patients and remote medical staff about unusual symptoms correlated to COVID-19 or similar diseases. The basic idea about measuring principle, system integration, digital signal processing and networking is presented and accompanied with preliminary testing results. The principle is not just simple and low cost, based on the components we use every day, but very immune to noise and artifacts.
F.08 Development and manufacture of a prototype
COBISS.SI-ID: 35662083The three-stage development of a cyber-physical speech-controlled wheelchair for disabled persons is described. Initially, a small prototype was built to test the feasibility of using cloud-based speech recognition systems for real-time wheelchair maneuvering. In the second stage, the full-sized prototype was built and tested in a laboratory and in a clinical environment. In the third stage, the full-scale prototype was equipped with distance sensors and an advanced control algorithm for semi-autonomous drive. The system architecture is described with the important addition of edge computing for speech recognition. Six cloud speech recognition services and two offline services were used, as using multiple speech recognition systems improves system reliability and latency. The software and hardware technologies are described, in addition to an innovative application of multiple cloud/edge systems for wheelchair motion control.
F.08 Development and manufacture of a prototype
COBISS.SI-ID: 8178451The development of group heart rate monitoring system based on ESP32 module has been described. The system architecture is described considering Wi-Fi, Blue Tooth and Blue Tooth Low Energy connection. The development of full stack prototype monitoring application is described. Power consumption measurements were performed. Short comparison between ESP8266 and ESP32 modules has been provided.
F.08 Development and manufacture of a prototype
COBISS.SI-ID: 8165395The problem of products’ terminal call rate (TCR) prediction during the warranty period is addressed in this paper. TCR represents the information on how much funds needs to be reserved for product repairs during the warranty period. So far, various methods have been used to address this problem, from discrete event simulation, time series, to machine learning predictive models. We address this problem by applying deep learning models to predict terminal call rate. For this purpose we have developed a series of deep learning models on a data set obtained by the manufacturer of home appliances and analysed their quality and performance. Results show that among all tested models, deep neural network with 6 layers and a convolutional neural network gave the best results. Deep learning is an approach worth further exploring, however, with the obstacle of requiring large volumes of quality data.
F.23 Development of new system-wide, normative and programme solutions, and methods
COBISS.SI-ID: 8125715High Performance Computing (HPC) enables solving complex problems that would be otherwise impossible to compute with ordinary desktop computers in an acceptable time. HPC services, offered in cloud, could foster new products and/or services development, faster time to market and optimization of production processes for Small and Medium sized enterprises (SME). However, cloud HPC services adoption among SMEs is still scarce and not all SMEs are viable to use HPC. The goal was to assess the cloud HPC potential among SMEs, select the viable SMEs and support them in implementation of the technology. For this purpose we have developed a web-based multi-criteria assessment tool to measure the potential of the SMEs to use cloud HPC services. In this paper we present the analysis of the 61 assessed organizations, among which 38 were SMEs.The analysis offers a limited insight into the state of the European SMEs and other organizations, but is important for understanding the needs and opportunities, that the cloud HPC services offer.
F.15 Development of a new information system/databases
COBISS.SI-ID: 8112915