LoRa Wireless Research Articles

Secure LoRa Wireless Communication for Soldier Tracking with the help of Interfacing Two Arduino Uno Devices in Military Operations

In this paper, a Secured LoRa Wireless Communication for Soldier Tracking with the help of Interfacing Two Arduino Uno Devices in Military Operations is presented in brief. This segment introduces a robust and highly secure wireless communication system built upon Long-Range (LoRa) technology, tailored for military applications. The proposed system leverages Arduino microcontrollers to establish a dependable data link between two remote military units, ensuring energy-efficient communication across extended distances. We delve into the system's design, implementation, and encryption methodologies employed to fortify data security. Rigorous testing and evaluation substantiate the system's capability to fulfill the stringent requirements of military communications, including long-range coverage, resilience to interference, and data confidentiality. This research significantly advances military communication technologies, providing a practical solution for safeguarded and efficient data exchange between deployed units. While this paper primarily focuses on long-distance communication, it also delves into the field of Automotive Wireless Communication, specifically Vehicle-to-Vehicle Communication, offering an introductory overview of the latter. The work carried out is the second semester mini-project by the students of Electronics & Communication Engineering under the guidance of the faculties.

Treatment and Disposal of Other Medical Wastes based on Bluetooth and LoRa Wireless IoT

With the maturity of the Internet of Things technology, medical institutions have established a positioning and sensing wireless IoT platform for the entire medical institution by using technologies such as Bluetooth positioning beacons, LoRa communication base stations, positioning and map engines. The intelligent medical waste collection and transfer vehicle integrates the wireless Internet of Things platform in the hospital based on 4G/5G modules, Bluetooth positioning terminals, electronic weighing and other technologies. An information-based, intelligent, and visualized "smart medical waste" management system covering all aspects of medical waste generation, collection, temporary storage, transfer, and disposal has been established in medical institutions. This set of solutions can greatly reduce the number of communication base stations deployed in hospital indoor buildings, the number of weak current construction and access switches in hospitals, save a lot of unnecessary costs for weak current construction and access switches and meet the real-time needs of intelligent medical waste collection and transfer vehicles such as real-time positioning, real-time tracking, video linkage, trajectory playback, and transfer route deviation alarms, which have certain reference significance in the practice of intelligent medical waste construction technology in hospitals based on smart IoT. The article describes one case of implementation of the technology in a university Hospital.

Edge Based Priority-Aware Dynamic Resource Allocation for Internet of Things Networks.

The exponential growth of the edge-based Internet-of-Things (IoT) services and its ecosystems has recently led to a new type of communication network, the Low Power Wide Area Network (LPWAN). This standard enables low-power, long-range, and low-data-rate communications. Long Range Wide Area Network (LoRaWAN) is a recent standard of LPWAN that incorporates LoRa wireless into a networked infrastructure. Consequently, the consumption of smart End Devices (EDs) is a major challenge due to the highly dense network environment characterised by limited battery life, spectrum coverage, and data collisions. Intelligent and efficient service provisioning is an urgent need of a network to streamline the networks and solve these problems. This paper proposes a Dynamic Reinforcement Learning Resource Allocation (DRLRA) approach to allocate efficient resources such as channel, Spreading Factor (SF), and Transmit Power (Tp) to EDs that ultimately improve the performance in terms of consumption and reliability. The proposed model is extensively simulated and evaluated with the currently implemented algorithms such as Adaptive Data Rate (ADR) and Adaptive Priority-aware Resource Allocation (APRA) using standard and advanced evaluation metrics. The proposed work is properly cross validated to show completely unbiased results.

A Method of Connecting Traditional Energy-Consuming Equipment to the Internet of Things

The concept of the Internet of things affects the way that people control electrical appliances. Moreover, due to the increasing importance of energy saving, the transformation of electrical power and energy system (EPES) is urgently needed. However, massive waste of energy caused by the inappropriate use of power-consuming equipment and most of the electrical devices controlled in traditional methods. This paper illustrates an Internet of Things (IoT) and edge computing (EC) technique to intellectualize standard energy-consuming equipment via LoRa wireless technology. The proposed system is low power and supports ad-hoc networks. Each node connects to the Internet via a LoRa based gateway. We mainly focus on controlling regular air conditioning and lighting system in office buildings via web pages, apps, etc. To simplify the process of installing the purposed node, several techniques were used to take over the control of traditional power-consuming equipment via user-side. The EC node can receive the short control command and operate itself according to the environment sensing results without control intelligence from cloud server. The experimental results indicate that our intellectualized network can work reliably and save energy-consuming equipment from wasting power.

Comparative Evaluation of the Performance of ZigBee and LoRa Wireless Networks in Building Environment

ZigBee and LoRa are communication technologies widely used in the application of the Internet of things (IoT), especially in the field of smart building environmental monitoring. The main purpose of this study is to compare and analyze the transmission performance of ZigBee and LoRa wireless communication networks in the building. Through two indicators of packet loss rate (PLR) and round-trip time (RTT), this paper discusses in detail the transmission performance of ZigBee and LoRa technologies in whole buildings under the same working conditions. We set up three experimental scenarios of line-of-sight, horizontal and vertical to evaluate the communication performance of these two networks by changing the baud rate and packet length, and cost and power consumption were considered. Experiments have shown that LoRa networks outperform ZigBee networks in most cases and are the best choice for building communication networks. The experimental results provide basic data support and engineering reference for the application of these two technologies in buildings, especially for the deployment of communication networks throughout buildings. The innovation and contribution of this paper are to discuss the effect of packet length, baud rate, distance, and different locations within a building on the performance of ZigBee and LoRa transmissions, using RTT and PLR as metrics through three experimental scenarios.

Optimization of LoRa SF Allocation Based on Deep Reinforcement Learning

LoRa is an IoT communication technology that realizes ultra-long-distance transmission through spread spectrum modulation. However, its ultra-long-distance transmission also sacrifices the corresponding rate, and data conflicts are prone to occur when the number of nodes is large. In this article, we investigate various types of data collisions in LoRa wireless work, most of which are affected by Spreading Factor (SF) assignment. At present, the distribution of the SF for LoRa in the industry is mostly based on Min-airtime and Min-distance. In the case of a large number of nodes, the data collision between nodes will increase sharply. This paper proposes a SF redistribution scheme under limited network resources, in order to improve the terminal capacity of the LoRa gateway. First, the problem of minimizing the data collision rate without expanding gateway or network resources is presented. Specifically, the reallocation of SF with increasing number of terminals is studied. Finally, considering the randomness of the data sent by the terminal, SF redistribution schemes based on deep reinforcement learning (DRL) are developed. The simulation results show that the collision rate of the proposed SF redistribution scheme is nearly 30% lower than Min-airtime and Min-distance, and its total energy consumption is close to Min-distance. Therefore, the proposed SF redistribution scheme can effectively improve the gateway capacity of LoRa wireless network.

A Solar-Rechargeable Radiation Dosimeter Design for Radiation Hazard Zone Located with LoRa Network

Since the nuclear energy leakage that occurred at the Fukushima nuclear power plant in Japan, people have paid more attention to the danger of environmental radiation. Environmental radiation is monitored using Geiger counters, which are not easy to obtain in some areas. Therefore, this research proposes an open-source and low-cost handheld Geiger counter that uses solar energy to charge lithium-ion batteries. Our design can provide a low-cost environmental radiation monitoring platform and effectively enhance the public’s scientific education awareness of radiation hazards. The measured dose rate can be output through the serial port, allowing a LoRa wireless network to transmit data to a database. When the sensing network deployed by the radiometer detects that the radiation value of the area is abnormally increased, it can issue an alarm to the government for the first time. Moreover, the low-power radiometer design can reduce energy consumption, reduce the burden on the ecological environment caused by the deployment of the sensing network, and provide sustainability for the environment.

Remotely Vital Signs Capturer for Older Adults Applied in Residential Zones

Assisted technology combined with sensor networks is an emerging technology for better homecare of people requiring specific support. In this work, we focus our attention on monitoring vital signs and accident prevention of older adults in residential areas without invasive and uncomfortable medical devices. We prototyped two vital signal monitoring devices integrated in structures deployed in common areas such as an arch and a bench. In addition, an alarm system was implemented to monitor residents in common areas and prevent vehicle accidents. The system was tested using Zigbee and LoRa wireless technologies and the network's overall performance was compared. In addition, the proposal was compared to commercially available medical equipment and results show a 96% similarity in vital signs monitoring. The system offers a silent noninvasive operation together with a friendly user interaction. It allows caregivers and family members to monitor vital signs of the residents remotely without the need of wearable specialized devices.

Development and performance analysis of a ZigBee and LoRa-based smart building sensor network

A wireless sensor network employing ZigBee and LoRa (Long Range) communication protocols for integration into smart building energy management systems is presented in this article. The design and implementation details are provided, and the performance parameters of the communication network are defined and analyzed based on the test results obtained from different configurations. The developed embedded system can be used in smart environments so that the room temperature, humidity, lighting systems, and so on can be automatically monitored and controlled. By customizing the embedded code, a variety of Internet of Things (IoT) applications can be introduced owing to their scalability. Taking advantage of the complementing low-power and long-range features of ZigBee and LoRa communication technologies, a system comprising an end device, a multi-protocol gateway, and a central data collector (CDC) unit is developed. The end device collects temperature and humidity as well as light intensity data using low-power sensors and sends the data to the gateway via the LoRa wireless transceiver module. The gateway was designed as an intermediate device that allows data exchange between the LoRa and ZigBee transceiver modules. It receives sensor data from the end device via LoRa and sends them to the CDC unit via a ZigBee-based XBee S2 commercial wireless transceiver module. Sensor data are monitored in the CDC unit by using an open-source IoT software platform. A commercial STM32 integrated circuit (IC) was used as a microcontroller unit for the end device and gateway. Performance parameters such as communication range and throughput data were studied for both the ZigBee and LoRa wireless transceiver modules.

Analysis of LoRaWAN Transactions for TEG-Powered Environment-Monitoring Devices

Long-Range (LoRa) transmission technology is potentially a suitable solution in abundant applications such as smart cities, smart industries, smart health, and others, although it is challenging and complex to implement. LoRa is a non-cellular modulation technology for Long-Range Wide-Area Networks (LoRaWAN) and is suitable for Internet of Things (IoT) solutions through its long-range and low-power consumption characteristics. The present paper provides a comprehensive analysis of LoRa wireless transactions through several measurements, which differ in LoRa parameter configuration. The results showed dependency of the power consumed by the transaction on the selected Effective Isotropic Radiated Power (EIRP). The quantity of energy consumed by the transaction also significantly depends on the selected data rate (combination of the spread factor and bandwidth) and payload.

LoRa-RL: Deep Reinforcement Learning for Resource Management in Hybrid Energy LoRa Wireless Networks

LoRa wireless networks are considered as a key enabling technology for next generation internet of things (IoT) systems. New IoT deployments (e.g., smart city scenarios) can have thousands of devices per square kilometer leading to huge amount of power consumption to provide connectivity. In this paper, we investigate green LoRa wireless networks powered by a hybrid of the grid and renewable energy sources, which can benefit from harvested energy while dealing with the intermittent supply. This paper proposes resource management schemes of the limited number of channels and spreading factors (SFs) with the objective of improving the LoRa gateway energy efficiency. First, the problem of grid power consumption minimization while satisfying the system's quality of service demands is formulated. Specifically, both scenarios the uncorrelated and time-correlated channels are investigated. The optimal resource management problem is solved by decoupling the formulated problem into two sub-problems: channel and SF assignment problem and energy management problem. Since the optimal solution is obtained with high complexity, online resource management heuristic algorithms that minimize the grid energy consumption are proposed. Finally, taking into account the channel and energy correlation, adaptable resource management schemes based on Reinforcement Learning (RL), are developed. Simulations results show that the proposed resource management schemes offer efficient use of renewable energy in LoRa wireless networks.

LoRa Based Wireless Weather Station

This research creates a weather station prototype using LoRa wireless technology. The internet of things (IoT) system is supported by LoRa, a wireless networking technology. This technology is an alternative to existing wireless communication modules such as GSM modules, Wi-Fi modules, and Bluetooth modules (BLE). The LoRa network is used to extend the range of wireless cells, allowing them to reach distances of up to 10 kilometers while consuming very little power. End devices can be connected to hundreds of nodes using a single LoRa network cell. Temperature, humidity, air pressure, rain detection, and wind speed are among the weather data that are monitored. The Atmega 328 microcontroller, DHT11 sensor, BH1750, rain sensor, BMP180 sensor, ESP32, LoRa module, solar panel, and web application are all included in the prototype. The number of end device nodes created in one cell is three. As a consequence, the system will be able to work correctly. With several types of sensors attached, this system has the potential to be applied in both urban and rural locations. Data collected from the sensors are then stored into the Firebase real-time database, a cloud-hosted database, and a mobile application is developed using MIT App Inventor to show the real-time weather conditions of a particular region in an android mobile phone. Keywords: Internet of Things (IoT), LoRa, MIT App Inventor, Sensors, Weather Parameters and, Wireless Station.

Energy Consumption Improvement of a Healthcare Monitoring System: Application to LoRaWAN

Recent advances in wireless communication technologies are having a great impact on people’s life, especially in the field of healthcare industry that provides a remote monitoring enabling medical staff to follow up the patient and diagnose his disease. LoRa wireless technology is becoming one of the most energetic effective solutions for Wireless Body Area Networks (WBANs) communications. In this work, we propose a LoRa-based low power healthcare WBAN platform called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HeaLoRa</i> for an adaptive patient monitoring process. Physicians can remotely monitor patient’s temperature, oxygen saturation level, blood pressure and heart rate to prevent any abnormality. Moreover, data acquisition and transmission are controlled based on a power consumption optimization strategy aiming to reduce redundant data. Based on the Early Warning Score (EWS), the system configuration is dynamically adapted, using a Fuzzy logic controller that makes the decision about the system sleep mode duration and the sent data rate. Furthermore, an analytical model of the energy consumption for acknowledged LoRa transmission is presented in this paper. The graphical abstract of the paper illustrates a medical application of a wireless body area network system where LoRa technology is used to transmit the data to a gateway then the data is transmitted to the doctor using IP based technology. By comparing with a reference system, the simulation results indicate that our system consumes 3 to 10 times less of energy depending on the studied scenario.

An improved communication resource allocation strategy for wireless networks based on deep reinforcement learning

With the advent of 5G networks, user demand for high-speed, low-latency, and high-reliability services continues to grow. When traditional communication technologies cannot meet the needs, wireless network LoRa technology has emerged. Although LoRa has low power consumption, Long-distance, and other advantages, terminal nodes still face frequent data collection and energy consumption issues how to more efficiently combine the deep reinforcement learning method for LoRa wireless network communication and allocate resources reasonably and effectively. This paper proposes a communication channel resource allocation strategy based on deep reinforcement learning, the CL-LoRa strategy. It uses extended preamble and low-power interception technologies to achieve on-demand synchronization and low-power communication. The basic idea of this strategy is to detect channel quality based on CAD, coordinate node scheduling, and wireless channel allocation. The node will choose different ways to acquire the channel according to the current network load, namely CSMA-CA competition and dynamic duty cycle communication. In this way, the channel utilization rate is improved, and the energy consumption problem of the long-distance communication data volume is perfectly solved. The duty cycle access method is based on the imbalance of energy consumption in the Internet of Things. It uses the remaining energy of the remote central node to dynamically adjust the duty cycle of the node, wake up the working time of the node, and send more beacons to the sleeping node. Reduce the sleep delay of the node. Through theoretical analysis of CL-LoRa protocol performance, compared with DDC-LoRa protocol and ADC-LoRa protocol, CL-LoRa protocol can increase channel utilization by 9%, reduce terminal energy consumption by 1.6%, and increase throughput by 1.5%.

Improved Indoor 3D Localization using LoRa Wireless Communication

New communication technologies are being developed for the Internet of Things (IoT), such as the wireless long distance and low power networks (LPWAN). The LoRa (Long Range) protocol, a wireless communication technology for long-range applications, is a type of LPWAN that has been recently widely used. The 3D localization and tracking of objects using LPWAN is a hotspot in IoT applications. In spite of many methods for improving the accuracy of 3D localization using traditional wireless communication such as Wi-Fi, ZigBee and Bluetooth, a few of them are available for long-range applications. In this way, this paper presents an improved 3D localization system based on LoRa communication and altimeter for indoor applications. The method uses the traditional trilateration technique with the signal strength indicator (RSSI) together with experimental update of parameters for improving the localization accuracy. Experimental tests were done in two indoor scenarios shown a significant improvement of up to 80%, with a maximum confident interval (95%) of 0,121m, in the 3D localization accuracy, in addition to better results than related papers in the literature.

Remote monitoring system for livestock environmental information based on LoRa wireless ad hoc network technology

The environmental quality of livestock houses is key to livestock breeding and directly affects the growth and health of animals. To target the characteristics of long application cycles and large coverage areas for environmental monitoring in large-scale livestock breeding, the current study designed a remote monitoring system to provide livestock environmental information based on LoRa wireless ad hoc network technology. The system consisted of collection terminals, control terminals, LoRa gateways, and Alibaba Elastic Compute Service. It realized real-time collection, wireless transmission, storage of multi-sensor node data, and remote control. The system was not limited by the selected time or region, because data interaction was achieved by accessing cloud servers using GPRS technology. Users could browse and obtain data from computers and a WeChat mini program from any location with network coverage. Additionally, the system used the improved receiver-based auto rate (RBAR) rate-adaptive algorithm in the LoRa wireless communication component. After application on a dairy farm, the results showed that the whole system collected 6140 sets of environmental data from four dairy houses. The packet loss rate was less than 1% within a communication distance of 604 m, and the communication success rate was greater than 99%. The control instructions were real-time and accurate, and the response time was less than 10 s, which met the remote control needs of large farms. The system provided powerful data and technical support for precision animal production. Keywords: remote monitoring, LoRa wireless ad hoc network, livestock environment, environment information, system DOI: 10.25165/j.ijabe.20221504.6708 Citation: Fu X, Shen W Z, Yin Y L, Zhang Y, Yan S C, Kou S L, et al. Remote monitoring system for livestock environmental information based on LoRa wireless ad hoc network technology. Int J Agric & Biol Eng, 2022; 15(4): 79–89.

Development and Implementation of Smart Water Metering System based on Lora Technology

The article presents an overview of traditional water meters in Vietnam, digitizing metrology technologies and wireless data transmission technology for data collection and user applications in smart water metering systems. After that, it is proposed to design a smart wireless water meter module. This paper focuses on designing and implementing a smart water meter to re-use traditional mechanical water meters by designing a smart water metering module attached to the existing meter. This way, it eliminates the costs of investing in flow water meter and influences the old water meter infrastructure system. The contribution of this paper is threefold: (i) Firstly, it proposes wireless data transmission and digitizing metrology technologies suitable for water metering systems in Viet Nam. (ii) Secondly, the proposed smart water meter module designs include hardware, firmwave, and plastic cover. There are two experimental prototypes of the module is introduced in this paper (iii) Lastly, The paper provides a water metering management software model for smart cities. And the overall systems of the proposed platform were built to verify the presented design. To reduce the amount of water leaking or users hacking from outside the meter in the measurement results, the article proposes to design features to alert about: abnormal flow, strong magnetic field influence, and equipment cover being removed. The experimental verification was designed with the Actaris water meter using Hall technology to digitize data and the Itron water meter with digitizing technology using the LC sensor. Besides, the Lora wireless network system is proposed and deployed to verify the water metering management with the advantages of low energy consumption, high security, and strict authentication process. Actual results for the laboratory environment and residential areas show that signal loss (RSSI) and signal noise (SNR) is within the allowable range. In addition, the packet loss rate &lt;1% and average power consumption meter &lt;50uA. Water metering management software is presented to verify the smart city service system.

An All-Textile Dual-Band Antenna for BLE and LoRa Wireless Communications

In this paper, a dual-band conductive textile-based wearable antenna operating at LoRa-868 MHz and BLE-2.4 GHz is presented. The proposed antenna is intended for accurate geolocation, tracking and communication applications in the military, industrial and telemedicine industries. The low-profile patch antenna is suitable for integrating into clothing. It is composed of three textile layers: top and bottom silver-ink-printed polystyrene fabrics, and a neoprene substrate. To utilize the flexible and restorable properties of these textile materials, the proposed antenna is directly fed by a flexible cable using an aperture-coupled feeding technique. This method not only eliminates the use of the conventional, bulky, and metallic SMA connector but also introduces a secondary resonance at 2.4 GHz, enabling the dual-band property. Using a thin coaxial cable fixed on the aperture slot for proximity coupling, a compact antenna size of 150 mm2 is obtained that can easily be attached and detached on existing cloths. The proposed structure has been fabricated and measured in an anechoic chamber to verify the performance. Measured gain of 3.28 dBi and 3.25 dBi was realized for LoRa and BLE at an antenna size of 0.61 λg × 0.61 λg × 0.012 λg (where λg is guided wavelength at 868 MHz) with a front-to-back ratio (FBR) of greater than 10 dBi.

Deep reinforcement learning based transmission policy enforcement and multi-hop routing in QoS aware LoRa IoT networks

The LoRa wireless connectivity has become a de facto technology for intelligent critical infrastructures such as transport systems. Achieving high Quality of Service (QoS) in cooperative systems remains a challenging task in LoRa. However, high QoS can be achieved via optimizing the transmission policy parameters such as spreading factor, bandwidth, code rate and carrier frequency. Yet existing approaches have not optimized the complete LoRa parameters. Furthermore, the star of stars topology used by LoRa causes more energy consumption and a low packet reception ratio. Motivated by this, this paper presents transmission policy enforcement and multi-hop routing for QoS-aware LoRa networks (MQ-LoRa). A hybrid cluster root rotated tree topology is constructed in which gateways follow a tree topology and Internet of Things (IoT) nodes follow a cluster topology. A ‘membrane’ inspired form the cell tissues which form clusters to sharing the correct information. The membrane inspired clustering algorithm is developed to form clusters and an optimal header node is selected using the influence score. Data QoS ranking is implemented for IoT nodes where priority and non-priority information is identified by the new field of LoRa frame structure (QRank). The optimal transmission policy enforcement uses fast deep reinforcement learning called Soft Actor Critic (SAC) that utilizes the environmental parameters including QRank, signal quality and signal-to-interference-plus-noise-ratio. The transmission policy is optimized with respect to the spreading factor, code rate, bandwidth and carrier frequency. Then, a concurrent optimization multi-hop routing algorithm that uses mayfly and shuffled shepherd optimization to rank routes based on the fitness criteria. Finally, a weighted duty cycle is implemented using a multi-weighted sum model to reduce resource wastage and information loss in LoRa IoT networks. Performance evaluation is implemented using a NS3.26 LoRaWAN module. The performance is examined for various metrics such as packet reception ratio, packet rejection ratio, energy consumption, delay and throughput. Experimental results prove that the proposed MQ-LoRa outperforms the well-known LoRa methods.

Research and Design of Adaptive Networking Method Based on LoRa

An adaptive networking method based on LoRa(Long Range) technology is proposed. The data transmission of wireless sensor networks widely used in the Internet of things is studied. A star network composed of Lora wireless transmission technology is designed to build an adaptive data transmission network. The design process of network topology, hardware and adaptive networking method of adaptive networking are introduced. Aiming at solving the problems of limited node capacity, adjacent frequency interference, and unreasonable channel resource allocation in the LoRa network, an adaptive frequency hopping mechanism is used for networking. The system uses I. MX6ULL as the main control and integrates 8 LoRa modules at the same time, which greatly improves the node capacity of the gateway. The server can realize real-time viewing and monitoring of node equipment, and real-time evaluation of channel communication quality.