Search Results (401)

The advancement of Automotive Industry 4.0 has promoted the development of Vehicle to Vehicle (V2V) and Internet of Vehicles (IoV) communication, which marks the new era for intelligent, connected and automated transportation. Despite the benefits of this metamorphosis in terms of effectiveness and convenience, new obstacles to safety, inter-connectivity, and cybersecurity emerge. The tire pressure monitoring system (TPMS) is one prominent feature that senses tire pressure, which is closely related to vehicle stability, braking performance and fuel efficiency. However, the majority of TPMSs currently in use are based on the use of insecure and proprietary wireless communication links that can be breached by attackers so as to interfere with not only tire pressure readings but also sensor data manipulation. For this purpose, we design a secure TPMS architecture suitable for real-time IoV sensing. The framework is experimentally implemented using a Raspberry Pi 3B+ (Raspberry Pi Ltd., Cambridge, UK) as an independent autonomous control unit (ACU), interfaced with vehicular pressure sensors and a LoRa SX1278 (Semtech Corporation, Camarillo, CA, USA) module to support low-power, long-range communication. The gathered sensor data are encrypted, their integrity checked, source authenticated by lightweight cryptographic algorithms and sent to a secure server locally. To validate this approach, we show a three-node exhibition where Node A (raw data and tampered copy), B (unprotected copy) and C (secure auditor equipped with alerting of tampering and weekly rotation of the ID) realize detection of physical level threats at top speeds. The validated datasets are further enriched in a MATLAB R2024a simulator by replicating the data of one vehicle by 100 virtual vehicles communicating using over 5G, LoRaWAN and LoRa P2P as communication protocols under urban, rural and hill-station scenarios. The presented statistics show that, despite 5G ultra-low latency, LoRa P2P consistently provides better reliability and energy efficiency and is more resistant to attacks in the presence of various terrains. Considering the lack of private vehicular 5G infrastructure and the regulatory restrictions, this work simulated and evaluated the performance of 5G communication, while LoRa-based communication was experimentally validated with a hardware prototype. The results underline the trade-offs among LoRa P2P and an infrastructure-based uplink 5G mode, when under some specific simulation conditions, as opposed to claiming superiority over all 5G modes. In conclusion, the presented Raspberry Pi–MATLAB hybrid solution proves to be an effective and scalable approach to secure TPMS in IoV settings, intersecting real-world sensing with large-scale network simulation, thus enabling safer and smarter next-generation vehicular systems. Full article

The rapid expansion of Long Range (LoRa) and Long Range Wide Area Network (LoRaWAN) protocol technologies in large-scale Internet of Things (IoT) deployments highlights the need for precise and analytically grounded energy consumption (EC) estimation of battery-powered LoRa end devices (DVs). Since LoRa DV instantaneous EC strongly depends on key transmission parameters, primarily including spreading factor (SF), transmit (Tx) power, and LoRa message packet size (PS), accurate modelling of their combined influence is essential for optimizing LoRa end DV lifetime, ensuring energy-efficient network operation, and supporting transmission parameter-adaptive communication strategies. Motivated by these needs, this paper presents a comprehensive multiple linear regression modelling framework for quantifying LoRa end DV EC during one transmission and reception LoRa end DV Class A communication cycle. The study is based on extensive high-resolution electric-current measurements collected over 69 measurement sets spanning different combinations of SFs, Tx power levels, and PS values. Based on measurement results, a total of 14 multiple linear regression models are developed, each capturing the joint impact of two transmission parameters while holding the third fixed. The developed regression models are mathematically formulated using linear, interaction, and polynomial terms to accurately express nonlinear EC behavior. Detailed statistical accuracy assessments demonstrate excellent goodness of fit of the developed EC multiple linear regression models. Complementary numerical analyses of regression models EC data distribution further validate regression models’ reliability, and highlight transmission parameter-driven variability of Lora end DV EC. The results of numerical analyses for LoRa end DV EC data distribution show that specific combinations of SF, Tx power, and PS transmit parameters amplify or mitigate EC differences, demonstrating that their joint variability patterns can significantly alter instantaneous energy demand across operating conditions. These interactions underscore the importance of modelling parameters together, rather than in isolation. The developed regression models provide interpretable mathematical formulations of instantaneous LoRa end DV EC prediction for transmission at different combinations of transmission parameters, and offer practical value for energy-aware configuration, battery-lifetime planning, and optimization of LoRa network-based IoT systems. Full article

Due to the development of the Internet of Things (IoT) and maritime wireless networks, the wireless networking of vessels will be the future trend. Furthermore, long-range (LoRa) technology is widely used in the marine field with the benefits of long range, lower power consumption, security, scalability, and robustness. In this study, LoRa is used as the solution for internal wireless networks of vessels as well as considering external and internal wireless communication, aiming to reduce construction and maintenance costs. The received signal strength (RSS) and signal to interference plus noise ratio (SINR) were measured and analyzed. The findings demonstrated that the mean value of the RSS and the SINR in the cockpit are above −81.70 dBm and 4.45 dB respectively, which indicates that there is a good communication link between the deck and the cockpit. Furthermore, the RSS value acquired by the nodes located on the same side of the gateway is stronger than that of the other nodes. Additionally, the RSS value acquired by the nodes close to the windows is found to be as high as 6–9 dB over that of the node located in the middle of the cockpit. Full article

The Satellite Internet of Things (IoT) sector is undergoing rapid transformation, driven by breakthroughs in satellite communications and the pressing need for seamless global coverage—especially in remote and poorly connected regions. In locations where terrestrial infrastructure is limited or non-existent, Low Earth Orbit (LEO) satellites are proving to be a game-changing solution, delivering low-latency and high-throughput links well-suited for IoT deployments. While North America currently dominates the market in terms of revenue, the Asia-Pacific region is projected to lead in growth rate. Nevertheless, the development of satellite IoT networks still faces hurdles, including spectrum regulation and international policy alignment. In this evolving landscape, the LoRa and LoRaWAN protocols have been enhanced to support direct communication with LEO satellites, typically operating at altitudes between 500 km and 2000 km. This paper offers a comprehensive review of current research on LoRa/LoRaWAN technologies integrated with LEO satellite systems, also providing a performance assessment of this combined architecture in terms of theoretical achievable bitrate, Bit Error Rate (BER), and path loss. The results highlight the main performance trends of LoRa LR-FHSS in direct-to-LEO links. Path loss increases sharply with distance, reaching approximately 150 dB at 500 km and 165–170 dB at 2000 km, significantly reducing achievable data rates. At 500 km, bitrates range from approximately 7–8 kbps for SF7 to below 2 kbps for SF12. BER follows a similar trend: below 200 km, values remain low (${10}^{-4}$–${10}^{-3}$) for all spreading factors. At 1000 km, BER rises to approximately $3.9\times {10}^{-3}$ for SF7 and $1.5\times {10}^{-3}$ for SF12. At 2000 km, BER reaches approximately $4.7\times {10}^{-2}$ for SF7 but stays below $2\times {10}^{-2}$ for SF12, showing a 2–$3\times$ improvement with higher spreading factors. Overall, many links exhibit path loss above 160 dB and BER in the ${10}^{-3}$–${10}^{-2}$ range at long distances. These results underscore the importance of adaptive spreading factor selection and LR-FHSS gain for reliable long-range satellite IoT connectivity, highlighting the trade-off between robustness and spectral efficiency. Full article

This article addresses the lack of low-cost, secure image-transmission solutions for IoT systems in remote environments. The design and implementation of a complete LoRa-based transmission system using ESP32 microcontrollers and Ebyte E220 modules, featuring AES-CBC encryption, HMAC integrity protection, and a custom retransmission protocol, are presented. The system achieves 100% packet delivery ratio (PDR) for 20 kB images over distances exceeding 2 km under line-of-sight conditions, with functional transmission up to 4.1 km. Image transmission time ranges from 35 s (0.1 m) to 110 s (600 m), while energy consumption increases from 4.95 mWh to 15.18 mWh. Critically, encryption imposes less than 1% overhead on total energy consumption. Unlike prior work focusing on isolated components, this article provides a complete, deployable architecture combining (i) low-cost hardware (<USD 50 total), (ii) long-range LoRa communication, (iii) custom reliability mechanisms for fragmenting 20 kB images into 100 packets, and (iv) end-to-end cryptographic protection, all evaluated experimentally across multi-kilometer distances. These findings demonstrate that secure long-range image transmission using commodity hardware is feasible and scalable for smart home and industrial monitoring applications. Full article

This work presents the development and evaluation of a low-cost and low-power IoT system for monitoring slope instabilities, rockfalls, and landslides using LoRa communication. The prototype integrates commercial ESP32-based hardware with an SX1276 transceiver, a triaxial MEMS accelerometer, and a GPS module for real-time tilt and location measurements. A tilt-estimation expression was derived from accelerometer data, enabling adaptation to different terrain inclinations. Laboratory tests were performed to validate the stability and accuracy of the inclination measurement, followed by outdoor LoRa range tests under mixed line-of-sight conditions. A lightweight dashboard was implemented for real-time visualization of GPS position, signal quality, and tilt data. The results show reliable tilt detection, consistent long-range communication, and low power consumption, highlighting the potential of the proposed prototype as a scalable and energy-efficient tool for geotechnical monitoring. Full article

Low Power Wide Area Networks (LPWAN) have emerged as essential connectivity solutions for the Internet of Things (IoT), addressing requirements for long range, energy efficient communication that traditional wireless technologies cannot meet. With LPWAN connections projected to grow at 26% compound annual growth rate until 2027, understanding real-world performance is crucial for technology selection. This review examines four leading LPWAN technologies—LoRaWAN, Sigfox, Narrowband IoT (NB-IoT), and LTE-M. This review analyzes 20 peer reviewed studies from 2015–2025 reporting real-world deployment metrics across power consumption, range, data rate, scalability, availability, and security. Across these studies, practical performance diverges from vendor specifications. In the cited rural and urban LoRaWAN deployments LoRaWAN achieves 2+ year battery life and 11 km rural range but suffers collision limitations above 1000 devices per gateway. Sigfox demonstrates exceptional range (280 km record) with minimal power consumption but remains constrained by 12 byte payloads and security vulnerabilities. NB-IoT provides robust performance with 96–100% packet delivery ratios at −127 dBm on the tested commercial networks, and supports tens of thousands devices per cell, though mobility increases energy consumption. In the cited trials LTE-M offers highest throughput and sub 200 ms latency but fails beyond −113 dBm where NB-IoT maintains connectivity. NB-IoT emerges optimal for large scale stationary deployments, while LTE-M suits high throughput mobile applications. Full article

The rising demand for long-range, low-power wireless communication in applications such as monitoring, smart metering, and wide-area sensor networks has emphasized the critical need for efficient spectrum utilization in LoRaWAN (Long Range Wide Area Network). In response to this challenge, this paper proposes a novel channel selection framework based on Hierarchical Discrete Pursuit Learning Automata (HDPA), aimed at enhancing the adaptability and reliability of LoRaWAN operations in dynamic and interference-prone environments. HDPA leverages a tree-structure reinforcement learning model to monitor and respond to transmission success in real-time, dynamically updating channel probabilities based on environmental feedback. Simulation results conducted in MATLAB R2023b demonstrate that HDPA significantly outperforms conventional algorithms such as Hierarchical Continuous Pursuit Automata (HCPA) in terms of convergence speed, selection accuracy, and throughput performance. Specifically, HDPA achieved 98.78% accuracy with a mean convergence of 6279 iterations, compared to HCPA’s 93.89% accuracy and 6778 iterations in an eight-channel setup. Unlike the Tug-of-War-based Multi-Armed Bandit strategy, which emphasizes fairness in real-world heterogeneous networks, HDPA offers a computationally lightweight and highly adaptive solution tailored to LoRaWAN’s stochastic channel dynamics. These results position HDPA as a promising framework for improving reliability and spectrum utilization in future IoT deployments. Full article

Phased antenna arrays have revolutionized modern wireless systems by enabling dynamic beamforming, multibeam synthesis, and user tracking to enhance data rates and reduce interferences, yet their reliance on expensive active components (e.g., phase shifters, amplifiers) embedded in antenna array elements limits adoption in cost-sensitive sub-GHz applications. Therefore, the active phased antenna arrays are still considered as high-end technology and primarily designed only for high-frequency bands and demanding applications such as radars and mobile base stations in microwave bands. In contrast, various important radio communication services still operate in sub-GHz bands with no adequate solution for modern antenna systems with beamforming capability. This paper introduces a 3D antenna array with switched-beam or multibeam capability, designed to eliminate mechanical rotators and active circuitry while maintaining all-sky coverage. By integrating collinear radiating elements with a Butler matrix feed network, the proposed 3D array achieves transmit/receive multibeam operation in the 435 MHz amateur satellite band and adjacent 433 MHz ISM band. Simulations demonstrate a design that provides selectable eight beams, enabling horizontal 360° coverage with only one radio connected to the Butler matrix. If eight noncoherent radios are used simultaneously, the proposed antenna array acts as a multibeam all-sky coverage antenna. Innovations in our design include a 3D circular collinear topology combining the broad and adjustable elevation coverage of collinear antennas with azimuthal beam steering, a passive Butler matrix enabling bidirectional transmit/receive multibeam operation, and scalability across sub-GHz bands where collinear antennas dominate (e.g., Lora WAN, trunked radio). Results show sufficient gain, confirming feasibility for low-earth-orbit satellite tracking or long-range IoT backhaul, and maintenance-free beamforming solutions in sub-GHz bands. Given the absence of practical beamforming or multibeam-capable solutions in this frequency band, our novel concept—featuring non-coherent cooperation across multiple ground stations and/or beams—has the potential to fundamentally transform how the growing number of CubeSats in low Earth orbit can be efficiently supported from the ground segment perspective. Full article

Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) is the newest modulation in LoRaWAN, designed to overcome the scalability and coverage limits of conventional LoRa. This study provides a real-world evaluation of LR-FHSS performance, benchmarking it directly against LoRa. An outdoor campaign was conducted in urban and semi-urban scenarios in and near the city of Castelldefels using a complete LR-FHSS-enabled network and an end-device transmitting at LoRa and LR-FHSS data rates (DRs). Measurements were collected along four diverse paths, capturing key metrics such as Received Signal Strength Indicator (RSSI) and Packet Delivery Ratio (PDR). The results clearly underline the advantages of LR-FHSS; while LoRa at DR0 and DR5 quickly lost connectivity beyond 1.5–2 km, LR-FHSS, particularly at DR8 and DR10, kept reliable links at 3–4 km. LR-FHSS robustness was most evident in non-line-of-sight (NLoS) and long-range scenarios. These findings highlight LR-FHSS as a strong candidate for future IoT deployments, offering extended range and higher robustness in challenging environments. Full article

LoRa has emerged as a cornerstone of low-power, long-range IoT communication. While highly effective for scalar sensing, its extension to multimedia remains constrained by limited bitrate, payload size, and duty-cycle regulations. This survey reviews research on multimedia transmission over LoRa, revealing that most current efforts are image-centric, with only a few preliminary studies addressing video or audio. We propose a structured taxonomy encompassing compression and fragmentation methods, cooperative and multi-hop architectures, MAC and cross-layer optimizations, and hybrid network designs. These strategies are analyzed in the context of IoT domains such as agriculture, surveillance, and environmental monitoring. Open challenges are highlighted in extending beyond static images, ensuring energy-efficient delivery, and developing spectrum- and ML-aware protocols. The survey provides IoT researchers with both a consolidated reference and a roadmap toward practical and scalable multimedia systems over LoRa. Full article

This paper investigates how key Long-Range (LoRa) sensor network transmission parameters and the number and material composition of physical obstacles on the signal propagation path impact wireless signal transmission quality in indoor propagation environments. A dedicated test platform was developed to assess how different combinations of the LoRa transmission parameters, which include spreading factor, transmit power, transmit duty cycle, message payload size, and the quantity and material composition of physical obstacles, with the signal propagation path length influence critical signal quality indicators, specifically the signal-to-noise ratio (SNR) and the received signal strength indicator (RSSI). The developed experimental test platform was implemented for a real-world indoor LoRa network composed of LoRa end devices (DVs) and gateways (GWs), utilizing technologies such as Node-RED for service orchestration, InfluxDB for data storage, The Things Network (TTN) for LoRa wide-area network connectivity, and Grafana for data visualization. The results of the performed analyses reveal how different combinations of LoRa transmission parameters, specifically the number and material composition of physical obstacles encountered during signal transmission among the LoRa end DVs and GWs, affect wireless signal quality indicators, namely RSSI and SNR, in indoor propagation environments of LoRa sensor networks. The obtained findings contribute to the optimization of LoRa transmission parameter selection for reliable and efficient signal transmission in LoRa indoor sensor network deployment, such as in urban environments with obstacles of varying structural composition and density encountered on the communication paths of different lengths between the LoRa end DVs and GWs. Full article

A Global Navigation Satellite System (GNSS) and Long Range (LoRa) technology play a crucial role in connected vehicles. The demand for antennas that cover both LoRa and GNSS bands is increasing. This work has developed a novel dual-band coplanar waveguide (CPW)-fed interleaved meander line antenna, incorporating a radiating element, ground plane, and feed. The antenna dimension is 90 × 90 × 1.635 mm³. The design employs a planar meander line configuration to effectively cover the 868 MHz LoRa and 1248 MHz GNSS bands. The antenna was integrated with a Frequency Selective Structure (FSS) to improve the parameters. The designed antenna provides sufficient bandwidth of 40 and 110 MHz for the LoRa and GNSS frequency bands, respectively. The CPW-interleaved meander line antenna attains a gain of −0.12 dBi at LoRa and 3.5 dBi at GNSS frequency. It achieves a voltage standing wave ratio of <2 and impedance of 50 Ω. The novelty of the proposed work is integrating FSS with a CPW-interleaved meander line antenna, which achieves dual-band operation. This dual-band low-profile configuration is suitable for connected vehicle communication. Full article

Plastic greenhouses, which account for the majority of protected horticulture facilities in East Asia, are highly susceptible to wind-induced uplift failures that can lead to severe structural and economic damage. To address this issue, this study developed a low-power and low-cost wireless monitoring system applying the concept of structural health monitoring (SHM) to greenhouse foundations. Each sensor node integrates a MEMS-based inertial measurement unit (IMU) for attitude estimation, a LoRa module for long-range alert transmission, and a microSD module for data logging, while a gateway relays anomaly alerts to users through an IP network. Uplift tests were conducted on standard steel-pipe foundations commonly used in plastic greenhouses, and the proposed sensor nodes were evaluated alongside a commercial IMU to validate attitude estimation accuracy and anomaly detection performance. Despite the approximately 30-fold cost difference, comparable attitude estimation results were achieved. The system demonstrated low power consumption, confirming its feasibility for long-term operation using batteries or small solar cells. These results demonstrate the applicability of low-cost IMUs for real-time structural monitoring of lightweight greenhouse foundations. Full article

In this paper, we present the design, prototyping, and working of a cost-effective, energy-efficient, and scalable air quality monitoring system (AQMS), enabled by a Low-power, long-Range Wide-Area Network (LoRaWAN), an Internet of Things (IoT) technology designed to provide connectivity for massive machine-type communication applications. The growing threat of air pollution necessitates outdoor and mobile environmental monitoring systems to provide real-time, location-specific data, which is unfortunately not possible using fixed monitoring devices. For our AQMS, we have developed two custom-built sensor nodes. The first node is equipped with a Nucleo-WL55JC1 microcontroller and sensors to measure temperature, humidity, and carbon dioxide (CO₂), while the other node is equipped with an Arduino MKR WAN 1310 controller with sensors to measure carbon monoxide (CO), ammonia (NH₃), and particulate matter (PM2.5 and PM10). These sensor nodes connect to a WisGate Edge LoRaWAN gateway, which aggregates and forwards the sensor data to The Things Network (TTN) for processing and cloud storage. The final visualization is handled via the Ubidots IoT platform, allowing for real-time visualization of environmental data. Besides environmental data, we were able to acquire a received signal strength indicator, signal-to-noise ratio, as well as a frame counter, which shows the number of packets received by the gateway. We performed laboratory testing, which confirmed reliable communication, with a packet delivery rate of 98% and a minimal average latency of 2.5 s. Both nodes operated efficiently on battery power, with the Nucleo-WL55JC1 consuming an average of 20 mA in active mode, while the Arduino MKR WAN 1310 operated at 15 mA. These values ensured extended operation for remote deployment. The system’s low power consumption and modular architecture make it viable for smart city applications and large-scale deployments in resource-constrained areas. Full article