# Proposed Fuzzy-NN Algorithm with LoRa Communication Protocol for Clustered Irrigation Systems
## 1 Introduction
Solar radiation and leaf wetness are also needed in order to calculate the dehydration of the plants and the evapotranspiration [11]. In order to avoid the installation cost of weather stations, it is provided that some irrigation systems collect weather data from weather websites [12]. Specifically, such systems require Internet access through a 3G/GPRS/4G transponder. Using the LTE network the system could have access not only to historical weather data, but to future prediction models as well. The main benefit of such systems is that they can postpone a scheduled irrigation if though weather prediction is known that we are going to have a rainfall. As web-based irrigation systems have continuous access to the Internet, they can be monitored and real-time controlled through a website or a smartphone [13]. Furthermore, alerts and notifications can be sent from the system to the end user. Another interesting category of smart irrigation systems is soil moisture sensor-based systems. Such systems measure the soil moisture using sensors [14] and decide whether irrigation is needed or not. Such systems are provided by companies such as Gardena [15] or Hunter [16] and implement static thresholds with delay transition irrigation algorithms. These systems are less accurate from the weather-based irrigation systems even if they measure soil humidity close to the plant root delivering plant water demands instantly. Their failure is mainly based on the implemented irrigation algorithms used. Another disadvantage of soil moisture systems compared to the weather system is that they cannot foresee future rainfalls or measure atmospheric conditions and provide an accurate prediction of plant water demands. Experimental soil moisture systems are also presented at [6; 17]. Authors at [17] suggest a new adaptive automatic irrigation system for arable areas, called Low-power long-Range Agriculture (LoRAgri). The LoRAgri system uses low-power long-range transceivers and gateways for data upload. Soil sensory adaptive systems' decisions are based on either a neural network or fuzzy algorithm that have as input periodically collected measurements from a number of soil moisture and temperature sensors set on the field [6]. Furthermore, a hybrid smart irrigation system that combines web-based services for weather prediction and soil moisture sensors for direct and precise moisture measurements near the roots of the plants is presented at [18]. In order to achieve a proper and efficient function of a smart irrigation system, a proper wireless communication system, capable of controlling the actuators and the sensors, is required. This capability is covered by the RFM69, IEE802.15.4 Zigbee [19; 20], LoRa and LoRaWaN technologies [21]. For deciding which wireless communication protocol is more suitable for IoT irrigation, many factors should be examined. Some of them are: cover range, power consumption, throughput, scalability, operational cost and security options. In terms of precision farming and irrigation, where the application areas may be located at distant places without a power supply, both the cover range and the power consumption are considered as critical factors. Table 1 shows the main characteristics of the wireless communication technologies mentioned. According to Table 1, if power consumption is acritical factor, then Bluetooth LE (BLE) is the best technology. The main drawback of BLE is its limited coverage. Next eligible choices are the ZigBee or 802.15.4 capable devices [19; 26]. IEEE 802.15.4 devices offer a cover range of 1000 m with 250 kbps throughput and current transmission consumption of about 65 mA [26]. If throughput is not as important as both high coverage and low power consumption, the most attractive technology is the narrowband, spread spectrum LoRa modulation or/and MAC layer LoRaWAN technology and infrastructure [27; 28]. It offers more than a 15 km cover range at 5 kbps throughput with only 40 mA current consumption at transmission.