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Crop productivity is highly dependent on the availability of soluble nitrogen (N), e.g. nitrate, in soil. When N levels are low, fertilisers are applied to replenish the soil's reserves. Typically the timing of these applications is based on paper-based guidance and sensor-based measurements of canopy greenness, which provides an indirect measure of soil N status. However this approach often means that N fertiliser is applied inappropriately or too late, resulting in excess N being lost to the environment, or too little N to meet crop demand. To promote greater N use efficiency and improve agricultural sustainability, we developed an Internet of Things (IoT) approach for the real-time measurement of soil nitrate levels using ion-selective membrane sensors in combination with digital soil moisture probes. The node incorporates state-of-the-art IoT connectivity using a LoRaWAN transceiver. The sensing platform can transfer real-time data via a cloud-connected gateway for processing and storage. In summary, we present a validated soil sensor system for real-time monitoring of soil nitrate concentrations, which can support fertiliser management decisions, improve N use efficiency and reduce N losses to the environment. [ABSTRACT FROM AUTHOR]

Indoor positioning systems are used to locate and track objects in an indoor environment. Distance estimation is done using received signal strength indicator (RSSI) of radio frequency signals. However, RSSI is prone to noise and interference which can greatly affect the accuracy performance of the system. In this paper Internet of Things (IoT) technologies like low energy Bluetooth (BLE), WiFi, LoRaWAN and ZigBee are used to obtain indoor positioning. Adopting the existing trilateration and positioning algorithms, the Kalman, Fast Fourier Transform (FFT) and Particle filtering methods are employed to denoise the received RSSI signals to improve positioning accuracy. Experimental results show that choice of filtering method is of significance in improving the positioning accuracy. While FFT and Particle methods had no significant effect on the positioning accuracy, Kalman filter has proved to be the method of choice for BLE, WiFi, LoRaWAN and ZigBee. Compared with unfiltered RSSI, results showed that accuracy was improved by 2% in BLE, 3% in WiFi, 22% in LoRaWAN and 17% in ZigBee technology for Kalman filtering method. [ABSTRACT FROM AUTHOR]

Long Range Wide Area Network (LoRaWAN) technology is rapidly expanding as a technology with long distance connectivity, low power consumption, low data rates and a large number of end devices (EDs) that connect to the Internet of Things (IoT) network. Due to the heterogeneity of several applications with varying Quality of Service (QoS) requirements, energy is expended as the EDs communicate with applications. The LoRaWAN Adaptive Data Rate (ADR) manages the resource allocation to optimize energy efficiency. The performance of the ADR algorithm gradually deteriorates in dense networks and efforts have been made in various studies to improve the algorithm's performance. In this paper, we propose a fuzzy-logic based adaptive data rate (FL-ADR) scheme for energy efficient LoRaWAN communication. The scheme is implemented on the network server (NS), which receives sensor data from the EDs via the gateway (GW) node and computes network parameters (such as the spreading factor and transmission power) to optimize the energy consumption of the EDs in the network. The performance of the algorithm is evaluated in ns-3 using a multi-gateway LoRa network with EDs sending data packets at various intervals. Our simulation results are analyzed and compared to the traditional ADR and the ns-3 ADR. The proposed FL-ADR outperforms the traditional ADR algorithm and the ns-3 ADR minimizing the interference rate and energy consumption. [ABSTRACT FROM AUTHOR]

Today, the role of smart machines in our lives is valuable. With the advancement of digital technologies, such as the internet of things (IoT), many embedded systems have been developed for various applications. In homes, all daily activities and even security depend on machines. Therefore, implementing IoT-based smart homes has become a prominent research field. Also, since we are in the era of endless growth of the IoT and its applications, the topic of home automation systems is becoming more popular due to its countless advantages. In general, most home automation systems focus on one function: the ability to control home appliances remotely. In the world of information technology, the creation of rules and standards should always be done in the early stages of development because, after the work is done, incompatibilities between devices are created, which is a severe challenge and limits the use of technology. Therefore, the research on IoT technology has led to the formation of various protocols; this article gives an overview of seven essential protocols. Also, in this review article, energy consumption management, and privacy and security issues are discussed, and smart homes are introduced as critical requirements for the evolution of smart cities. [ABSTRACT FROM AUTHOR]

Water is essential for ensuring food security in the world, and agriculture is by far the largest consumer of the earth's available freshwater. Food demand and world’s population are expected to increase over the next years. However, climate change will continue to affect water resources and make the problem of food security more complex. Therefore, agriculture must be smarter and agricultural water management must be more efficient and sustainable. This paper presents a low-cost and smart irrigation system based on LoRa technology to better manage irrigation water at field scale. The system essentially consists of a set of nodes distributed on the field for irrigation control and monitoring of soil parameters, a complete weather station for measuring climate data and a remote server for remote decision-making support. The weather station is connected to the internet via a gateway and the measured climatic data are collected and stored regularly on a server, where access to data is provided by a confidential service. The remote server allows the user to select the irrigation mode and method and to store the soil condition variables collected by the wireless sensor network in order to process them for a more optimal management of irrigation. The irrigation system also allows to compute the Penman–Monteith reference evapotranspiration (ET0) on the daily scale, turn on or off the pump remotely, and automatically fill the water tank. Based on our experimental tests, the low investment cost and the high energy autonomy make the proposed irrigation system more suitable for off grid areas with limited water resources.

Internet of Things (IoT) devices increasingly contribute to critical infrastructures, necessitating robust security measures. LoRaWAN, a low-power IoT network, employs the Advanced Encryption Standard (AES) with a 128-bit key for encryption and integrity, balancing efficiency and security. As computational capabilities of devices advance and recommendations for stronger encryption, such as AES-256, emerge, the implications of using longer AES keys (192 and 256 bits) on LoRaWAN devices’ energy consumption and processing time become crucial. Despite the significance of the topic, there is a lack of research on the implications of using larger AES keys in real-world LoRaWAN settings. To address this gap, we perform extensive tests in a real-world LoRaWAN environment, modifying the source code of both a LoRaWAN end device and open-source server stack to incorporate larger AES keys. Our results show that, while larger AES keys increase both energy consumption and processing time, these increments are minimal compared to the time on air. Specifically, for the maximum payload size we used, when comparing AES-256 to AES-128, the additional computational time and energy are, respectively, 750 ms and 236 μJ. However, in terms of time on air costs, these increases represent just 0.2% and 0.13%, respectively. Our observations confirm our intuition that the increased costs correlate to the number of rounds of AES computation. Moreover, we formulate a mathematical model to predict the impact of longer AES keys on processing time, which further supports our empirical findings. These results suggest that implementing longer AES keys in LoRaWAN is a practical solution enhancing its security strength while not significantly impacting energy consumption or processing time.

LoRaWAN is a communication protocol designed especially for Internet of Things (IoT) applications that offers benefits such as long-distance connection and low power consumption. Due to the characteristics of LoRaWAN, this technology has gained great popularity in various IoT applications, such as environmental monitoring, smart agriculture, and applications in the areas of health and mobility, among others. Given this situation, the objective of this work is to provide an in-depth overview of LoRaWAN technology in terms of its applications, as well as the devices that have been used for the development of such applications. Additionally, this work reviews what other areas of LoRaWAN have been covered in different scientific articles, i.e., performance improvement and security. Among the main results of this study though analyzing previous works, we can say that most of them have been developed in the area of environmental monitoring and have used low-cost devices such as Arduinos, Raspberry Pis, and relatively low-cost commercial products such as those of the Semtech and STMicroelectronics brands. The analysis of the present work shows objectively and formally that LoRaWAN technology can be applied in various applications and that there are many studies that try to optimize its performance and security. This paper seeks to identify and describe the most relevant applications of LoRaWAN in different sectors, such as agriculture, health, and environmental monitoring, among others, and the challenges and solutions found in each area. This literature review will provide a valuable reference to understand the potential and opportunities offered by LoRaWAN technology.

The Internet of Things (IoT) enables us to gain access to a wide range of data from the physical world that can be analyzed for deriving critical state information. In this regard, machine learning (ML) is a valuable tool that can be used to develop models based on observed physical data, leading to efficient analytical decisions, including anomaly detection. In this work, we address some key challenges for applying ML in IoT applications that include maintaining privacy considerations of user data that are needed for developing ML models and minimizing the communication cost for transmitting the data over the IoT network. We consider a representative application of the anomaly detection of ECG signals that are obtained from a set of low-cost wearable sensors and transmitted to a central server using LoRaWAN, which is a popular and emerging low-power wide-area network (LPWAN) technology. We present a novel framework utilizing federated learning (FL) to preserve data privacy and appropriate features for uplink and downlink communications between the end devices and the gateway to optimize the communication cost. Performance results obtained from computer simulations demonstrate that the proposed framework leads to a 98% reduction in the volume of data that is required to achieve the same level of performance as in traditional centralized ML.

The transit service in a city should be the most efficient, least polluting, most accessible, and sustainable means of transportation for its citizens. However, serious shortcomings have been detected, mainly in medium-sized cities in developing countries. These shortcomings are related to a lack of user information, insecurity, low service availability, and repeated stops in inappropriate and/or unauthorized places. Some of these shortcomings contribute to high accident rates and traffic congestion. The development of tools to improve the characteristics and conditions of transit service in cities has become an imperative need to improve the quality of life of citizens and city sustainability. Transit service tracking is relevant in aspects such as online location information to travelers and control by transport companies for compliance with speed limits, schedules, routes, and stops. This research proposes a transit vehicle tracking system based on the Internet of Vehicles (IoV) in Vehicle-to-Roadside (V2R) classification. The proposed system is ideal for the use of electric vehicles due to the low power consumption of the tracking device. This system uses Intelligent Transportation Systems (ITS) tracking service architecture, Long Range (LoRa) communication technology, and its LoRa Wide Area Network (LoRaWAN) protocol. Additionally, the system offers real-time location prediction in the absence of position data. The IoV tracking device integrates a GPS-LoRa module card with an Inertial Measurement Unit (IMU). A location prediction algorithm was implemented to train and store a prediction model with previously collected data from tracking devices. To evaluate the developed model, a case study in the city of Popayán (Colombia) was implemented, using three routes for testing. The results of the system implementation were satisfactory, obtaining an average coverage of 60.4% of the routes in the final field tests through LoRa communication. For the remaining 39.6% of the routes, location data prediction was used, with an average accuracy of 177 m with respect to the real location. Considering the obtained results, a tracking system such as the one proposed in this article can be used in the transit systems of medium-sized cities in developing countries to improve service quality and fleet control.

A number of technological application factors can be highlighted in smart city solutions, where small data and long-range transmission are of primary consideration. These include monitoring energy consumption, operating a smart waste management system, monitoring, and tracking traffic, having smart parking systems, monitoring public lighting, and even detecting various malfunctions. Such smart city systems use IoT technology for data collection. An essential aspect of urban solutions is to ensure the coverage of large areas, both outdoors and indoors, low energy consumption, as well as modularity and mobility. LPWAN technologies can meet these conditions. LPWAN technologies include LTE-M, NB-IoT, LoRaWAN, and Sigfox. Using LoRaWAN technology can be the right solution for these cases. As with any application, it is crucial to clarify the challenges of the application with LoRaWAN. The present study addresses the categorization of LoRaWAN devices and the challenges of technology in smart city solutions. LoRaWAN products used in smart city solutions can be grouped according to several aspects. This article deals with the creation of classifications that facilitate further testing. Smart city application challenge studies are applied to the specified categories. The challenges of the solutions cover several areas. These include technological aspects, aspects of specifications, and aspects of the nature of the application. Another area represents the information security aspects, which is, however, not addressed by this invention. Based on these aspects, the article describes the challenges of LoRaWAN technology in smart cities.

Reducing energy consumption in networks of IoT devices is very important. This paper presents the results of experimental studies of the proposed method of reducing power consumption for the protective gateway of the industrial network. Research was conducted for devices built on Lora modules. The LoRa Modem Calculator software from Semtech was used as a modeling tool. The recommended values of the program registers are given to achieve optimal energy consumption parameters for data reception and transmission modes. Information about the prototype is given and its practical implementation is shown. The developed prototype of the gateway implements the “Protocol Transformation” method, which allows removing possible dangerous inserts from the data packets received by the gateway. This can improve the security of packets from the gateway to IoT devices and back, and thus the network as a whole.

Transient stability and supply disturbances are common yet unwelcome phenomena in power distribution systems, particularly in sub-Saharan Africa. The growing demand for greater reliability and dependability in power delivery has aroused the interest of researchers and renewed the pursuit of advanced technological solutions for fault detection and location determination at medium and low-voltage levels. The length of the distribution network typically ranges from hundreds to thousands of kilometers. In this regard, the management of distribution networks, including the identification of faulty segments, is a significant recurrent challenge facing power-system operators. With the ever-expanding distribution network and regulatory demands for service reliability, the challenge for network operators is daunting. However, the deployment of IoT technologies in the energy distribution infrastructure would significantly accelerate the detection and location of faults, thus transforming the electricity delivery service into one that is responsive, communicative, attractive, and robust. This study proposes, designs, and implements a reasonably priced LoRaWAN-based IoT platform for monitoring distribution networks. The study was conducted in Nakuru County, Kenya on an actual and active distribution network owned and managed by Kenya Power Company. Experimental results showed that a trigger is generated at the network-monitoring center in about 100 ms of the occurrence of a fault on the distribution network, thus enabling quick, prompt, and immediate commencement of reparative action. Furthermore, practical evaluation has shown that this platform is well adapted for the context of developing countries where budgetary constraints and cost prohibitions hinder the upgrade of the legacy grid into fully-fledged smart entities.

The arrival of IoT has brought constant innovation. This innovation has allowed many “things” (sensors, wearable devices, smart appliances, among others) to be connected to the Internet to deliver the information they collect. This need for connection has set the tone for the development of new protocols that adapt to the IoT environment, taking into consideration low energy consumption and low computational cost. These protocols are known as Low Power Wide Area Network (LPWAN). In this context, one of the most used is LoRaWAN. As many other IoT protocols, it is exposed to security threats. These threats aim to compromise security principles like confidentiality, integrity and availability (CIA Triad) of the information. This paper aims to analyze weaknesses related to gateways within LoRaWAN infrastructure to propose a lightweight security protocol to address gateway authentication vulnerabilities. This protocol uses lightweight cryptographic functions to achieve this goal as it is intended to be deployed over IoT devices which are very limited in terms of hardware and power resources. Likewise, this protocol has gone through a formal security analysis with the use of BAN-Logic and a tool called Scyther, to validate the security of the proposed protocol.

Low Power Wide Area Networks (LPWAN) have emerged as an attractive Internet of Things (IoT) communication option. When deploying a communication network to support IoT applications, large coverage and low power consumption are critical requirements. Despite the fact that existing LPWAN technology solutions promote IoT requirements such as long communication range, energy efficiency, scalability, and low cost, network performance is a major concern. With so many LPWAN technologies available, there is a growing interest in evaluating them. Recent works have presented various comparison studies of LPWAN technologies, but the majority of them have approached the analysis from the standpoint of comparing technical specifications rather than presenting measurement results obtained from network deployment scenarios. We argue that by proposing a comparative evaluation from an experimental standpoint, the comparison discussion is deepened. This paper proposes an experimental comparative evaluation of LoRaWAN and SigFox, two emerging LPWAN technologies operating in sub-GHz Industrial, Scientific, and Medical (ISM) frequency bands, based on coverage and energy-efficiency test performance. The experimental evaluation was proposed first by identifying coverage and energy-efficiency as the two most important design goals for LPWAN applications. Second, by proposing test performance to evaluate those goals, where extensive measurements were made in network deployments, and finally, by highlighting the main performance findings in both networks for comparison purposes. The results show that in a fair-weather test, LoRaWAN outperformed SigFox in terms of coverage, achieving a higher packet delivery rate (PDR $\gtrsim ~80$ %), and having higher radio strength signal (RSSI $\gtrsim $ -110 dBm). Sigfox, on the other hand, shows better energy efficiency with 20% more sent messages under the same test conditions.

Low Power Wide Area Networks have emerged as a leading communications technology in the field of Internet of Things sensor and monitoring networks. In such networks, uplink traffic is characterized as a combination of periodic data reports and event-triggered alarm reports. When an many devices detect an event in a short timespan, a burst of concurrent transmissions can occur, leading to a surge of collisions, and thus severe data delivery performance degradation. In this paper, a hybrid random/scheduled access strategy is proposed for mitigating the impact of traffic-triggering events on network performance. Under periodic report traffic the LoRaWAN standard Class A protocol is in effect, but after an event a TDMA scheme is applied. Three implementations of this strategy are described. The first is a pair of novel MACs for LoRaWAN, allowing (a) synchronization of end devices with the network using the event detection as a crude synchronization point, and (b) the dynamic scheduling of groups of devices. The other two implementations build upon a single-hop and a two-hop previously proposed LoRaWAN-based wake-up architectures, respectively. The above approaches are validated and studied through extensive simulation. The results show improved packet delivery ratio over the Class A MAC. The effect is more prominent as the event propagation velocity increases. The proposed approach also surpasses LoRaWAN in energy per delivered bit for high event propagation velocities. Finally, the novel protocol has a lower hardware and deployment complexity than the wake up radio based alternatives, at the cost of higher energy consumption.

Landslides are a frequent natural hazard during the rainy season, causing infrastructural and economic damage globally. Several studies on landslide monitoring techniques have been conducted in order to reduce various types of losses. There is an extensive review in this article of the ground monitoring method that uses a variety of sensors and some of the primary advances that help to enhance architecture and fulfill user needs. Study of cost-effective ground monitoring technique analysis in different landslide warning systems and some known cases in research article based on coverage area and energy harvesting methods also discussed. Moreover, WSN architecture identified and creates classes according to their benefits and drawbacks as well as performance is evaluated such as efficiency, reliability, quality of service, and network lifetime.

Satellites are going to revolutionize the Internet of Things (IoT) connectivity enabling the ubiquitous coverage targeted by 5G and upcoming 6G networks. While the potentials of satellite IoT are unquestionable, many challenges still remain unsolved. In the present work, we design a Long Range Wide Area Network (LoRaWAN) with mobile gateways (GWs) installed on Low Earth Orbit (LEO) satellites. We address synchronization issues due to intermittent link availability between the End Devices (EDs) and the GW, and we propose a Scheduling Algorithm for LoRa to LEO Satellites (SALSA). SALSA ensures reliable communication, avoiding packets drops and packet collisions, by using a Time Division Multiple Access (TDMA) approach, rather than classic ALOHA-based LoRa. The uplink transmissions of the EDs are scheduled considering the satellite availability period, the satellite footprint, and the specific visit time for each ED. Two different policies are proposed: a First Come First Served (FCFS), and a FAIR policy. Simulation results, obtained in real conditions, with real satellites visibility, demonstrate the better performance achievable with SALSA (regardless of the policy) compared to standard LoRa. The FAIR policy outperforms the FCFS policy by giving all the EDs an equal chance to transmit, even to those that are visited last by the satellite. The performance of SALSA can be further improved considering larger constellations of LEO satellites.

Cloud Radio Access Networks (Cloud-RANs) have recently emerged as a promising architecture to meet the increasing demands and expectations of future wireless networks. Such an architecture can enable dynamic and flexible network operations to address significant challenges, such as higher mobile traffic volumes and increasing network operation costs. However, the implementation of compute-intensive signal processing Network Functions (NFs) on the General Purpose Processors (General Purpose Processor) that are typically found in data centers could lead to performance complications, such as in the case of overloaded servers. There is therefore a need for methods that ensure the availability and continuity of critical wireless network functionality in such circumstances. Motivated by the goal of providing highly available and fault-tolerant functionality in Cloud-RAN-based networks, this paper proposes the design, specification, and implementation of live migration of containerized Baseband Units (BBUs) in two wireless network settings, namely Long Range Wide Area Network (LoRaWAN) and Long Term Evolution (LTE) networks. Driven by the requirements and critical challenges of live migration, the approach shows that in the case of LoRaWAN networks, the migration of BBUs is currently possible with relatively low downtimes to support network continuity. The analysis and comparison of the performance of functional splits and cell configurations in both networks were performed in terms of fronthaul throughput requirements. The results obtained from such an analysis can be used by both service providers and network operators in the deployment and optimization of Cloud-RANs services, in order to ensure network reliability and continuity in cloud environments.

The constant evolution in communication infrastructures will enable new Internet of Things (IoT) applications, particularly in areas that, up to today, have been mostly enabled by closed or proprietary technologies. Such applications will be enabled by a myriad of wireless communication technologies designed for all types of IoT devices, among which are the Long-Range Wide-Area Network (LoRaWAN) or other Low-power and Wide-Area Networks (LPWAN) communication technologies. This applies to many critical environments, such as industrial control and healthcare, where wireless communications are yet to be broadly adopted. Two fundamental requirements to effectively support upcoming critical IoT applications are those of energy management and security. We may note that those are, in fact, contradictory goals. On the one hand, many IoT devices depend on the usage of batteries while, on the other hand, adequate security mechanisms need to be in place to protect devices and communications from threats against their stability and security. With thismotivation in mind, we propose a solution to address the management, in tandem, of security and energy in LoRaWAN IoT communication environments. We propose and evaluate an architecture in the context of which adaptation logic is used to manage security and energy dynamically, with the goal of guaranteeing appropriate security, while promoting the lifetime of constrained sensing devices. The proposed solution was implemented and experimentally evaluated and was observed to successfully manage security and energy. Security and energy are managed in line with the requirements of the application at hand, the characteristics of the constrained sensing devices employed and the detection, as well as the threat, of particular types of attacks.

Long-range (LoRa) communication has attracted much attention recently due to its utility for many Internet of Things applications. However, one of the key problems of LoRa technology is that it is vulnerable to noise/interference due to the use of only up-chirp signals during modulation. In this paper, to solve this problem, unlike the conventional LoRa modulation scheme, we propose a modulation scheme for LoRa communication based on joint up- and down-chirps. A fast Fourier transform (FFT)-based demodulation scheme is devised to detect modulated symbols. To further improve the demodulation performance, a hybrid demodulation scheme, comprised of FFT- and correlation-based demodulation, is also proposed. The performance of the proposed scheme is evaluated through extensive simulation results. Compared to the conventional LoRa modulation scheme, we show that the proposed scheme exhibits over 3 dB performance gain at a bit error rate of 10−4.

Low-Power Wide-Area Network (LPWAN) is a new type of wireless technology that offers long range communication for devices in the Internet of Things (IoT) and LoRaWAN is one of the main technologies currently available to enable LPWAN environments. In the LoRaWAN architecture, the Join Server is a key component and is responsible for security tasks, such as authentication and key management. However, the Join Server acts as a Single Point of Failure (SPOF) since all encryption keys are stored centrally. Then, this paper presents a secure and fault-tolerant architecture to increase the levels of security and availability in LoRaWAN. A permissioned blockchain and smart contracts are used to replace the Join Server and solve the SPOF problem. A working prototype was created using open-source tools in order to evaluate the feasibility of the proposed architecture. Additionally, the performance of a blockchain network was analyzed in a cloud environment under multiple workloads and fault-tolerance experiments were performed to evaluate the impact of network failures. The results show a trade-off between availability and performance when choosing the number of blockchain peers in small scenarios. However, this behavior is reversed in large scenarios where the performance of multiple peers is best suited.

Direct-to-Satellite IoT (DtS-IoT) is a promising approach to deliver data transfer services to IoT devices in remote areas where deploying terrestrial infrastructure is not appealing or feasible. In this context, low-Earth orbit (LEO) satellites can serve as passing-by IoT gateways to which devices can offload buffered data to. However, transmission distances and channel dynamics, combined with highly constrained devices on the ground makes of DtS-IoT a very challenging problem. Here, we present LoRa-based approaches to realize scalable and energy-efficient DtS-IoT. Our study includes the Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) physical layer, currently on the roadmap of future space IoT projects. Specifically, we propose uplink transmission policies that exploit satellite trajectory information. These schemes are framed with a theoretical Mixed Integer Linear Programming (MILP) model providing an upper bound on performance as well as inspiration for scheduled DtS-IoT solutions. Simulation results provide compelling evidence that trajectory based policies can duplicate the amount of IoT nodes, while specific variants can further boost the scalability by 30% without incurring energy penalties. We also quantify that LR-FHSS can improve the deployment scalability by a factor of 75x at the expenses of 30% higher device’s power consumption compared to the legacy LoRa modulation.

Fleet Management Control Systems (FMCS) monitor vehicles in real-time and help assessing schedule compliance. Transit services in developing countries must improve in aspects such as information about routes, schedules and users; and compliance with traffic regulations, to achieve an increase in their demand. Although a FMCS can deal with these issues, currently implemented systems have some limitations related to communications technology, associated costs, interoperability and standardization. This paper includes the following: 1) The Intelligent Transportation System (ITS) architecture designed for the FMCS; 2) The development of a FMCS prototype for developing countries, considering the proposed architecture, using the Long Range communication technology and Intelligent Transportation Systems services; 3) A validation and testing of the FMCS prototype, using transit vehicles in a city. The developed prototype was successfully tested. The ideal operating parameters of the FMCS in terms of communications technology were identified in one of the four routes used in the tests. The results in such route were validated with additional tests, using the same parameters, and reaching similar operating values. A data set with the information of the performed tests was generated. With the results obtained in the FMCS, a better control of the transit service can be achieved, helping to improve upon the problems identified for developing countries (especially in medium-sized cities) related to route and schedule compliance, speeding, safety, standardization and helpful information for users. Additionally, service operation costs are reduced by using cutting-edge communications technology and promoting interoperability with other mobility services created for these cities.

In recent years, fire detection technologies have helped safeguard lives and property from hazards. Early fire warning methods, such as smoke or gas sensors, are ineffectual. Many fires have caused deaths and property damage. IoT is a fast-growing technology. It contains equipment, buildings, electrical systems, vehicles, and everyday things with computing and sensing capabilities. These objects can be managed and monitored remotely as they are connected to the Internet. In the Internet of Things concept, low-power devices like sensors and controllers are linked together using the concept of Low Power Wide Area Network (LPWAN). Long Range Wide Area Network (LoRaWAN) is an LPWAN product used on the Internet of Things (IoT). It is well suited for networks of things connected to the Internet, where terminals send a minute amount of sensor data over large distances, providing the end terminals with battery lifetimes of years. In this article, we design and implement a LoRaWAN-based system for smart building fire detection and prevention, not reliant upon Wireless Fidelity (Wi-Fi) connection. A LoRa node with a combination of sensors can detect smoke, gas, Liquefied Petroleum Gas (LPG), propane, methane, hydrogen, alcohol, temperature, and humidity. We developed the system in a real-world environment utilizing Wi-Fi Lora 32 boards. The performance is evaluated considering the response time and overall network delay. The tests are carried out in different lengths (0–600 m) and heights above the ground (0–2 m) in an open environment and indoor (1st Floor–3rd floor) environment. We observed that the proposed system outperformed in sensing and data transfer from sensing nodes to the controller boards. [ABSTRACT FROM AUTHOR]

With the development of electronics and communication techniques, the interest in realizing sensor networks with a large number of end nodes is growing. The main idea is to install devices in remote locations without direct supervision, which requires an uninterrupted power supply and secure communication to the rest of the network. In this paper, an experimental comparative analysis of popular practical LoraWAN end nodes (WisNode RAK811 and Seeeduino SX1301) regarding energy consumption in different security modes, spreading factors, energy consumption in sleep/idle mode as well as the security keys extraction from memory was performed. [ABSTRACT FROM AUTHOR]