Experimental Study on Low Power Wide Area Networks (LPWAN) for Mobile Internet of Things

In the past decade, we have witnessed explosive growth in the number of low-power embedded and Internet-connected devices, reinforcing the new paradigm, Internet of Things (IoT). The low power wide area network (LPWAN), due to its long-range, low-power and low-cost communication capability, is actively considered by academia and industry as the future wireless communication standard for IoT. However, despite the increasing popularity of `mobile IoT', little is known about the suitability of LPWAN for those mobile IoT applications in which nodes have varying degrees of mobility. To fill this knowledge gap, in this paper, we conduct an experimental study to evaluate, analyze, and characterize LPWAN in both indoor and outdoor mobile environments. Our experimental results indicate that the performance of LPWAN is surprisingly susceptible to mobility, even to minor human mobility, and the effect of mobility significantly escalates as the distance to the gateway increases. These results call for development of new mobility-aware LPWAN protocols to support mobile IoT.Comment: To appear at 2017 IEEE 85th Vehicular Technology Conference (VTC'17 Spring

A Wearable Fall Detection System based on LoRa LPWAN Technology

Several technological solutions now available in the market offer the possibility of increasing the independent life of people who by age or pathologies otherwise need assistance. In particular, internet-connected wearable solutions are of considerable interest, as they allow continuous monitoring of the user. However, their use poses different challenges, from the real usability of a device that must still be worn to the performance achievable in terms of radio connectivity and battery life. The acceptability of a technology solution, by a user who would still benefit from its use, is in fact often conditioned by practical problems that impact the person’s normal lifestyle. The technological choices adopted in fact strongly determine the success of the proposed solution, as they may imply limitations both to the person who uses it and to the achievable performance. In this document, targeting the case of a fall detection sensor based on a pair of sensorized shoes, the effectiveness of a real implementation of an Internet of Things technology is examined. It is shown how alarming events, generated in a metropolitan context, are effectively sent to a supervision system through Low Power Wide Area Network technology without the need for a portable gateway. The experimental results demonstrate the effectiveness of the chosen technology, which allows the user to take advantage of the support of a wearable sensor without being forced to substantially change his lifestyle

A Comparative Analysis on IoT Communication Protocols for Future Internet Applications

With the emergence of 5G, the Internet of Things (IoT) will bring about the next industrial revolution in the name of Industry 4.0. The communication aspect of IoT devices is one of the most important factors in choosing the right device for the right usage. So far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. And most of them are wireless protocols due to the sheer number of device requirements for IoT. In this paper, we summarize the network architectures of some of the most popular IoT wireless communications protocols. We also present them side by side and provide a comparative analysis revolving around some key features, including power consumption, coverage, data rate, security, cost, and Quality of Service (QoS). This comparative study shows that LTE-based protocols like NB-IoT and LTE-M can offer better QoS and robustness, while the Industrial, Scientific, and Medical (ISM) Band based protocols like LoRa, Sigfox, and Z-wave claim their place in usage where lower power consumption and lesser device complexity are desired. Based on their respective strengths and weaknesses, the study also presents an application perspective of the suitability of each protocol in a certain type of scenario and addresses some open issues that need to be researched in the future. Thus, this study can assist in the decision making regarding choosing the most suitable protocol for a certain field

Autonomous Collision Avoidance in Small Scale Vehicles

The undergraduate research performed in this study focused on autonomous collision avoidance in small scale vehicles. The goal of this study was to find equipment to build a fully autonomous small scale vehicle for use in different applications. Radio frequency communication, ultrasonic sensors, and single board computers were used to create an autonomous vehicle for multiple applications. Different communication protocols and sensors were investigated, and an explanation was specified concerning the hardware choice. The main communication protocol tested was Long Range Wide Area Network, and the main electronics tested and used were ultrasonic sensors, First Person View cameras, and the Arduino Mega 2560. Though the main communication protocol performed worse than anticipated, a different communication protocol was chosen and tested. The secondary communication protocol produced more promising results

A Systematic Review of LPWAN and Short-Range Network using AI to Enhance Internet of Things

Artificial intelligence (AI) has recently been used frequently, especially concerning the Internet of Things (IoT). However, IoT devices cannot work alone, assisted by Low Power Wide Area Network (LPWAN) for long-distance communication and Short-Range Network for a short distance. However, few reviews about AI can help LPWAN and Short-Range Network. Therefore, the author took the opportunity to do this review. This study aims to review LPWAN and Short-Range Networks AI papers in systematically enhancing IoT performance. Reviews are also used to systematically maximize LPWAN systems and Short-Range networks to enhance IoT quality and discuss results that can be applied to a specific scope. The author utilizes selected reporting items for systematic review and meta-analysis (PRISMA). The authors conducted a systematic review of all study results in support of the authors' objectives. Also, the authors identify development and related study opportunities. The author found 79 suitable papers in this systematic review, so a discussion of the presented papers was carried out. Several technologies are widely used, such as LPWAN in general, with several papers originating from China. Many reports from conferences last year and papers related to this matter were from 2020-2021. The study is expected to inspire experimental studies in finding relevant scientific papers and become another review

A neural network propagation model for LoRaWAN and critical analysis with real-world measurements

Among the many technologies competing for the Internet of Things (IoT), one of the most promising and fast-growing technologies in this landscape is the Low-Power Wide-Area Network (LPWAN). Coverage of LoRa, one of the main IoT LPWAN technologies, has previously been studied for outdoor environments. However, this article focuses on end-to-end propagation in an outdoor–indoor scenario. This article will investigate how the reported and documented outdoor metrics are interpreted for an indoor environment. Furthermore, to facilitate network planning and coverage prediction, a novel hybrid propagation estimation method has been developed and examined. This hybrid model is comprised of an artificial neural network (ANN) and an optimized Multi-Wall Model (MWM). Subsequently, real-world measurements were collected and compared against different propagation models. For benchmarking, log-distance and COST231 models were used due to their simplicity. It was observed and concluded that: (a) the propagation of the LoRa Wide-Area Network (LoRaWAN) is limited to a much shorter range in this investigated environment compared with outdoor reports; (b) log-distance and COST231 models do not yield an accurate estimate of propagation characteristics for outdoor–indoor scenarios; (c) this lack of accuracy can be addressed by adjusting the COST231 model, to account for the outdoor propagation; (d) a feedforward neural network combined with a COST231 model improves the accuracy of the predictions. This work demonstrates practical results and provides an insight into the LoRaWAN’s propagation in similar scenarios. This could facilitate network planning for outdoor–indoor environments

Low Power Wide Area Networks (LPWAN): Technology Review And Experimental Study on Mobility Effect

In the past decade, we have witnessed explosive growth in the number of low-power embedded and Internet-connected devices, reinforcing the new paradigm, Internet of Things (IoT). IoT devices like smartphones, home security systems, smart electric meters, garage parking indicators, etc., have penetrated deeply into our daily lives. These IoT devices are increasingly attached and operated in mobile objects like unmanned vehicles, trains, airplanes, etc. The low power wide area network (LPWAN), due to its long-range, low-power and low-cost communication capability, is actively considered by academia and industry as the future wireless communication standard for IoT. However, despite the increasing popularity of mobile IoT, little is known about the suitability of LPWAN for those mobile IoT applications in which nodes have varying degrees of mobility. To fill this knowledge gap, in this thesis:1. We present a thorough review on LPWAN technology focusing on the mobility effect. 2. We conduct an experimental study to evaluate, analyze, and characterize LPWAN in both indoor and outdoor mobile environments.Our experimental results indicate that the performance of LPWAN is surprisingly susceptible to mobility, even to minor human mobility, and the effect of mobility significantly escalates as the distance to the gateway increases. These results call for development of new mobility-aware LPWAN protocols to support mobile IoT