Empirical propagation models are vital tools for planning and deployment of any wireless communication network as they depend less on terrain data and are faster to execute. In this paper, NS3 is used to simulate radio propagation for Long range wide area network (LoRaWAN) at 868 MHz in an urban environment using the Okumura-Hata model, the COST-231 Hata, and the COST 231 Walfish-Ikegami (COST-WI). The predicted received signal strength values are compared with the real-world measurements taken in the city of Glasgow to analyse the validity and accuracy of the empirical models, when used for planning of radio-coverage in LoRaWAN networks. The comparison between models and measurements shows that Okumura-Hata under-estimated the received signal strength in Glasgow city scenario while COST-WI over-estimated the same power. Similarly, Okumura-Hata model showed higher accurate predictions whereas COST-WI accuracy was the least. Magnitude of mean absolute error indicates how big or small models prediction error can be expected. This study can be used to give an insight into the effectiveness and accuracy of empirical propagation models for evaluation of Internet of Things (IoT) connectivity with LoRaWAN networks in a non-line of sight (NLOS) urban environment.

Long-range, low-power wide area network (Lo-RaWAN) is a very scalable solution for the Internet of Things (IoT). Performance evaluation of LoRaWAN in Urban environments is a challenging task. Theoretical modeling results have been inaccurate. In this paper, a trace-driven simulation for LoRaWAN 868 MHz propagation was performed using GPS data and their corresponding received signal level. The dataset has been extracted from 5015 datasets of LoRaWAN measurements taken from Glasgow city center. ICS-Telecom was used to simulate the real-world measurement environment. Comparison of trace-simulated results and the real-world data is performed to evaluate the prediction accuracy of Deygout 94, ITU-R 525/526 and COST-Walfish Ikegami (COST-WI) propagation models. All models over-estimated LoRaWAN trace-simulated received signal strength (RSS) levels in comparison to real-world collected samples. While Deygout 94 prediction accuracy was higher with mean absolute error (MAE) at 0.83 and standard deviation (SD) at 4.17, COST-WI performed poorly with MAE and SD at 2.87 and 10.96 respectively.

Biometric authentication systems are believed to be effective compared to traditional authentication systems. The introduction of biometrics into smart cards is said to result into biometric-based smart ID card with enhanced security. This paper discusses the biometric-based smart ID card with a particular emphasis on security and privacy implications in Rwanda universities environment. It highlights the security and implementation issues. The analysis shows that despite the necessity to implement biometric technology, absence of legal and regulatory requirements becomes a challenge to implementation of the proposed biometric solution. The paper is intended to engage a broad audience from Rwanda universities planning to introduce the biometric-based smart ID cards to verify students and staff for authentication purpose.

Little work has been reported on the magnitude and impact of interference with the performance of Internet of Things (IoT) applications operated by Long-Range Wide-Area Network (LoRaWAN) in the unlicensed 868 MHz Industrial, Scientific, and Medical (ISM) band. The propagation performance and signal activity measurement of such technologies can give many insights to effectively build long-range wireless communications in a Non-Line of Sight (NLOS) environment. In this paper, the performance of a live multi-gateway in indoor office site in Glasgow city was analysed in 26 days of traffic measurement. The indoor network performances were compared to similar performance measurements from outdoor LoRaWAN test traffic generated across Glasgow Central Business District (CBD) and elsewhere on the same LoRaWAN. The results revealed 99.95% packet transfer success on the first attempt in the indoor site compared to 95.7% at the external site. The analysis shows that interference is attributed to nearly 50 X greater LoRaWAN outdoor packet loss than indoor. The interference measurement results showed a 13.2–97.3% and 4.8–54% probability of interfering signals, respectively, in the mandatory Long-Range (LoRa) uplink and downlink channels, capable of limiting LoRa coverage in some areas.

Long-range, Low-Power Wide Area Network (LoRaWAN) is a very scalable solution for the Internet of Things (IoT). Due to the air channel environment's complexity, connectivity is a crucial parameter for successfully planning and deploying the IoT networks. Measurements and simulations have been used to evaluate LoRaWAN propagation models in the Urban environment, but it is a challenging task. While practical propagation evaluation has been prohibitively expensive, the theoretical modeling results have been less accurate. This paper uses real-world measurements and a trace-driven simulation technique to evaluate the RF propagation models' prediction performance for LoRaWAN 868 MHz propagation. First, a novel LoRaWAN tracedriven simulation of Glasgow city centre has been performed. Second, LoRaWAN 868 MHz measurements have been used to perform a critical analysis of LoRaWAN trace-driven Radio Frequency (RF) propagation models and validation. The processed trace dataset is composed of GPS coordinates, and the corresponding LoRaWAN received signal strength. The dataset has been extracted from 5017 datasets of LoRaWAN measurements taken from Glasgow city centre. A trace simulation program built-in ICS-Telecom was used to simulate LoRaWAN propagation in the real-world urban environment. Comparison of LoRaWAN simulation traces and the real-world data was performed to evaluate the prediction performance accuracy of Deygout 94, ITU-R 525/526, and COST-Walfish Ikegami (COST-WI) propagation models. All models overestimated LoRaWAN trace-simulated RSS levels in comparison to collected measurement samples. While Deygout 94 prediction accuracy was higher with mean absolute error (MAE) at 0.83 dBm and standard deviation (SD) at 4.17 dBm, COST-WI performed poorly with MAE and SD at 2.87 dBm and 10.96 dBm respectively.