# Overcoming Limitations of LoRa Physical Layer in Image Transmission
## 1 Introduction  
Wireless remote sensing (WSN) technologies vary in their ability to transfer data at low powers, high speeds, and over long ranges. Today, low-power wide-area networks (LPWANs) are the ideal WSN technology as their extended coverage, low cost, and energy saving features (which are possible without the need for communication infrastructure [1]) make them complementary to short-range wireless technologies, such as Wi-Fi and Bluetooth Low Energy, and credible alternatives to cellular technology, for urban-scale Internet of Things (IoT) applications. This ability for long-range communication to thousands of devices (star topologies) at a low cost and limited power consumption is due to improvements in duty cycling and networking protocols [2]. Long Range (LoRa), narrowband IoT (NB-IoT), IEEE 802.15.4, Sigfox and LTE-M are examples of recent LPWAN technologies used by (IoT) applications to connect wireless sensors to extend the deployment of the IoT and reduce power consumption.  
One of the most important features of LPWANs is the ability to enhance the signal-to-noise ratio (SNR) at the receiver by narrowing its bandwidth or by spreading the energy of the signal over a widerfrequency range. For example, in NB-IoT, narrowing the bandwidth to less than 25 kHz increases the SNR and enhances the performance of the transceiver. A similar effect is possible with Sigfox when the bandwidth is reduced to approximately 100 Hz. With LoRa, narrowing the bandwidth of a receiver enables the decoding of transmissions with signal amplitudes 19.5 dB below the noise floor, consequently enabling communication at longer ranges than other techniques. The capability for long range communication with LoRa characterizes it as the future network infrastructure for advanced IoT applications, since it can connect hundreds of IoT end-devices to one gateway, and does not need special requirements to connect to other existing networks. In this paper, we demonstrate the first application of LoRa in a WSN for transferring images of mangrove forests captured by an image sensor and used for mangrove monitoring in the Sabak Bernam district of Malaysia (see Figure 1). Currently GPP (2G/3G) technology by Ericsson Co. [3] used to monitor the status of the mangrove trees by reading data from soil moisture, smoke, sea level measurements, and temperature sensors. Subsequently, these data transferred to the community center and processed to develop strategies to prevent the degradation of the mangrove forest. Using LoRa as a WSN with Image sensors for the first time in this area beside it will help in the environment monitoring process, it will contribute in adding LPWAN capabilities of reducing power consumption (powered by batteries for years), cost of installation (no need for more expensive equipment) and increase the range of transferring data (see Figure 2 for more information).  
The rest of the paper is structured as follows. First a LPWAN image transferring related works is discussed. Then, a background is provided about LoRa network and some important parameters dictating its operation. After this, a comparison is done between LoRa and other LPWAN technologies which highlights the advantages of this technique for WSN applications. After this, details of the novel image transfer experiment and how it was set up are discussed. We subsequently list and discuss the results of this experiment, to verify the viability of image transfer over the LoRa physical layer. Our results indicate that LoRa is an ideal technology for mangrove monitoring WSN.