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

Survey on wireless technology trade-offs for the industrial internet of things

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

Development and Implementation of a Hybrid Wireless Sensor Network of Low Power and Long Range for Urban Environments

The urban population, worldwide, is growing exponentially and with it the demand for information on pollution levels, vehicle traffic, or available parking, giving rise to citizens connected to their environment. This article presents an experimental long range (LoRa) and low power consumption network, with a combination of static and mobile wireless sensors (hybrid architecture) to tune and validate concentrator placement, to obtain a large coverage in an urban environment. A mobile node has been used, carrying a gateway and various sensors. The Activation By Personalization (ABP) mode has been used, justified for urban applications requiring multicasting. This allows to compare the coverage of each static gateway, being able to make practical decisions about its location. With this methodology, it has been possible to provide service to the city of Malaga, through a single concentrator node. The information acquired is synchronized in an external database, to monitor the data in real time, being able to geolocate the dataframes through web mapping services. This work presents the development and implementation of a hybrid wireless sensor network of long range and low power, configured and tuned to achieve efficient performance in a mid-size city, and tested in experiments in a real urban environment.Spanish project RTI2018-093421-B-I0

Empirical verification of network coverage plans for LoRaWAN IoT infrastructures

openThe Industrial Internet of Things (IoT) has rapidly grown in recent years, leading to the adoption of Low Power Wide Area Networks (LPWAN) in important infrastructures such as energy, water and gas distribution systems. LPWAN technologies, which operate in the unlicensed radio frequency spectrum, offer a promising solution for implementing Advanced Metering Infrastructures (AMI). This thesis focuses on a key challenge in deploying AMI LPWAN, which is strategically placing and installing gateway devices to ensure optimal coverage for smart meters. By addressing this challenge, the research aims to optimize LPWANs for the efficient implementation of AMI in large-scale critical infrastructures.The Industrial Internet of Things (IoT) has rapidly grown in recent years, leading to the adoption of Low Power Wide Area Networks (LPWAN) in important infrastructures such as energy, water and gas distribution systems. LPWAN technologies, which operate in the unlicensed radio frequency spectrum, offer a promising solution for implementing Advanced Metering Infrastructures (AMI). This thesis focuses on a key challenge in deploying AMI LPWAN, which is strategically placing and installing gateway devices to ensure optimal coverage for smart meters. By addressing this challenge, the research aims to optimize LPWANs for the efficient implementation of AMI in large-scale critical infrastructures

Performance Evaluation of LoRaWAN for Green Internet of Things

LoRa is a long-range, low power and single-hop wireless technology that has been envisioned for Internet of Things (IoT) applications having battery driven nodes. Nevertheless, increase in number of end devices and varying throughput requirements impair the performance of pure Aloha in LoRaWAN. Considering these limitations, we evaluate the performance of slotted Aloha in LoRaWAN using extensive simulations. We employed packet error rate (PER), throughput, delay, and energy consumption of devices under different payload sizes and varying number of end devices as benchmarks. Moreover, an analytical analysis of backlogged and non-backlogged under slotted Aloha LoRaWAN environment is also performed. The simulation shows promising results in terms of PER and throughput compared to the pure Aloha. However, increase in delay has been observed during experimental evaluation.Finally, we endorse slotted aloha LoRaWAN for Green IoT Environment

Design and experimental validation of a LoRaWAN fog computing based architecture for IoT enabled smart campus applications

A smart campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university campus. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability. The technologies employed so far to cope with such a scenario are not yet able to manage simultaneously all the previously mentioned demanding requirements. Nevertheless, recent paradigms such as fog computing, which extends cloud computing to the edge of a network, make possible low-latency and location-aware IoT applications. Moreover, technologies such as Low-Power Wide-Area Networks (LPWANs) have emerged as a promising solution to provide low-cost and low-power consumption connectivity to nodes spread throughout a wide area. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is one of the most recent developments, receiving attention both from industry and academia. In this article, the use of a LoRaWAN fog computing-based architecture is proposed for providing connectivity to IoT nodes deployed in a campus of the University of A Coruña (UDC), Spain. To validate the proposed system, the smart campus has been recreated realistically through an in-house developed 3D Ray-Launching radio-planning simulator that is able to take into consideration even small details, such as traffic lights, vehicles, people, buildings, urban furniture, or vegetation. The developed tool can provide accurate radio propagation estimations within the smart campus scenario in terms of coverage, capacity, and energy efficiency of the network. The results obtained with the planning simulator can then be compared with empirical measurements to assess the operating conditions and the system accuracy. Specifically, this article presents experiments that show the accurate results obtained by the planning simulator in the largest scenario ever built for it (a campus that covers an area of 26,000 m2), which are corroborated with empirical measurements. Then, how the tool can be used to design the deployment of LoRaWAN infrastructure for three smart campus outdoor applications is explained: a mobility pattern detection system, a smart irrigation solution, and a smart traffic-monitoring deployment. Consequently, the presented results provide guidelines to smart campus designers and developers, and for easing LoRaWAN network deployment and research in other smart campuses and large environments such as smart cities.This work has been funded by the Xunta de Galicia (ED431C 2016-045, ED431G/01), the Agencia Estatal de Investigación of Spain (TEC2016-75067-C4-1-R) and ERDF funds of the EU (AEI/FEDER, UE)

LPWA-based IoT Technology Selection for Smart Metering Deployment in Urban and Sub Urban Areas: A State Electricity Company Perspective

The need for LPWA-based Internet of Things (IoT) technology for deploying smart metering services is rapidly growing for its ability to manage energy usage in real-time and increase efficiency. However, the problem faced by electric utility companies is how to choose the most appropriate technology. This study uses a techno-economic approach to compare the two most widely used technological alternatives, namely establishing LoRaWAN as a non-licensed LPWA technology or leasing NB-IoT as a licensed LPWA technology owned by a telecommunications operator. Case studies conducted in the urban area of Bandung and sub-urban city of Tasikmalaya as an example of a typical town in Indonesia. The results showed that LoRaWAN and NB-IoT are both technically and business feasible to be implemented with their respective advantages. LoRaWAN is superior in battery lifetime, business model, speed of implementation, and total costs, whereas NB-IoT is superior in range, capacity, quality of service, security, and ecosystem support. Using PLN's perspective as a national electricity company in Indonesia, LoRaWAN has a Net Present Value of 23% higher than NB-IoT in the 10th year