LoRaWAN Network for Fire Monitoring in Rural Environments

Sendra, Sandra; García, Laura; Lloret, Jaime; Bosch, Ignacio; Vega-Rodríguez, Roberto

doi:10.3390/electronics9030531

Cited by 55 publications

(55 citation statements)

References 30 publications

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“…Since sub-GHz LoRa devices are very limited in terms of their number of possible transmissions—i.e., to comply with duty cycle regulations—they are typically used for applications that do not require frequent communication. For example, Sendra et al proposed a LoRa-based forest fire detection system that transmits sensor measurements every 28 min [ 1 ]. Besides this, the long-range communication benefit of sub-GHz LoRa has been exploited to provide emergency services in GPS-less environments [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

LoRa 2.4 GHz Communication Link and Range

Janssen

BniLam

Aernouts

et al. 2020

Sensors

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Recently, Semtech has released a Long Range (LoRa) chipset which operates at the globally available 2.4 frequency band, on top of the existing sub-GHz, km-range offer, enabling hardware manufacturers to design region-independent chipsets. The SX1280 LoRa module promises an ultra-long communication range while withstanding heavy interference in this widely used band. In this paper, we first provide a mathematical description of the physical layer of LoRa in the 2.4 band. Secondly, we investigate the maximum communication range of this technology in three different scenarios. Free space, indoor and urban path loss models are used to simulate the propagation of the 2.4 LoRa modulated signal at different spreading factors and bandwidths. Additionally, we investigate the corresponding data rates. The results show a maximum range of 333km in free space, 107m in an indoor office-like environment and 867m in an outdoor urban context. While a maximum data rate of 253.91 can be achieved, the data rate at the longest possible range in every scenario equals 0.595. Due to the configurable bandwidth and lower data rates, LoRa outperforms other technologies in the 2.4 band in terms of communication range. In addition, both communication and localization applications deployed in private LoRa networks can benefit from the increased bandwidth and localization accuracy of this system when compared to public sub-GHz networks.

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Section: Introductionmentioning

confidence: 99%

LoRa 2.4 GHz Communication Link and Range

Janssen

BniLam

Aernouts

et al. 2020

Sensors

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“…In our system, a reliable and user-friendly architecture for communicating within the devices has been proposed. As an example, the LoRA and IoT based system presented in [52] has used a server which is costly. As our proposed system can communicate directly between sender and receiver, the cost is low.…”

Section: Key Performance Metrices Analysismentioning

confidence: 99%

Smart Monitoring and Controlling of Appliances Using LoRa Based IoT System

Nur-A-Alam

Ahsan

Based

et al. 2021

Designs

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In the era of Industry 4.0, remote monitoring and controlling appliance/equipment at home, institute, or industry from a long distance with low power consumption remains challenging. At present, some smart phones are being actively used to control appliances at home or institute using Internet of Things (IoT) systems. This paper presents a novel smart automation system using long range (LoRa) technology. The proposed LoRa based system consists of wireless communication system and different types of sensors, operated by a smart phone application and powered by a low-power battery, with an operating range of 3–12 km distance. The system established a connection between an android phone and a microprocessor (ESP32) through Wi-Fi at the sender end. The ESP32 module was connected to a LoRa module. At the receiver end, an ESP32 module and LoRa module without Wi-Fi was employed. Wide Area Network (WAN) communication protocol was used on the LoRa module to provide switching functionality of the targeted area. The performance of the system was evaluated by three real-life case studies through measuring environmental temperature and humidity, detecting fire, and controlling the switching functionality of appliances. Obtaining correct environmental data, fire detection with 90% accuracy, and switching functionality with 92.33% accuracy at a distance up to 12 km demonstrated the high performance of the system. The proposed smart system with modular design proved to be highly effective in controlling and monitoring home appliances from a longer distance with relatively lower power consumption.

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“…Traditional methods for fire detection rely on sensors that require close proximity for activation, such as infrared and optical sensors [2]. For example, in [3], the authors proposed a prototype for fire monitoring in rural environments. It collects data from several long range (LoRa) nodes of sensors that measure temperature, relative humidity, wind speed and CO2 of the environment.…”

Section: Introductionmentioning

confidence: 99%

A Privacy-Preserving Iot-Based Fire Detector

et al. 2021

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Fire detection has been an issue of interest to researchers due to its significant damage to lives and property within a very short time. One of the recent solutions developed to detect fire is to use Internetof-Things (IoT) devices equipped with cameras for surveillance. The captured videos of surroundings may be processed by the IoT devices themselves or at the cloud. The latter case is required if the detection algorithm is computationally demanding. However, the use of cloud has a flaw. In fact, using the cloud could pose the threat of having the privacy of a place violated, either through hacking or unauthorized access to the footage of the place where the cloud is installed. In this paper, a fire detection system that preserves the privacy of surroundings, while maintaining a high level of accuracy for fire detection is proposed. The proposed system makes use of the cloud for fire detection; and that is achieved by sending to the cloud features extracted from the video captured by the IoT device, instead of sending the actual footage. Binary video descriptors and Convolutional Neural Network (CNN) have been used to develop the fire detection algorithm. The video descriptors are used to extract features, while the CNN is used for classification. Videos with real fire and non-fire scenes have been used in this development. Results show that the performance of proposed fire detection algorithm can achieve 97.5% classification accuracy, that outperforms the state-of-the art algorithms which make direct use of raw videos. Therefore, the proposed fire detector is as reliable as other available systems, with the advantage of having a privacy-preserving capability. It is also demonstrated that the proposed video descriptors can be implemented for real-time processing using an IoT device, Raspberry Pi 4 platform, with an average processing speed of 100ms per frame, which well satisfies practical needs.

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LoRaWAN Network for Fire Monitoring in Rural Environments

Cited by 55 publications

References 30 publications

LoRa 2.4 GHz Communication Link and Range

LoRa 2.4 GHz Communication Link and Range

Smart Monitoring and Controlling of Appliances Using LoRa Based IoT System

A Privacy-Preserving Iot-Based Fire Detector

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