# Grapevine Downy Mildew Warning System Based on NB-IoT and Energy Harvesting Technology
## 1 Introduction
Technologies such as LoRaWAN [6] and Sigfox are used in non-licensed bands of the frequency spectrum. In the licensed spectrum covered by mobile network operators (MNOs), the Narrowband Internet of Things technology (NB-IoT) [7; 8] has emerged, with the advance of the Long Term Evolution (LTE) and issuing of 3 GPP standard Release 13 [9]. NB-IoT has been in use for a few years, with several hardware platforms available (for example, U-blox SARA-R410 and Quectel BC-68/95 modules). NB-IoT uses star topology where all the sensor nodes are directly connected to the LTE cellular base station acting like a concentrator or the'sink node' in WSN terminology. The underlying network core performs all the necessary data processing. On the other hand, the WSN uses multi-hop communications and distributed systems in most applications. Figure 1 illustrates an example of the NB-IoT system. This shows the end-to-end NB-IoT details of connection for a reliable and efficient communication system between the two end points: a wireless sensor node and a cloud application. At the physical level, the wireless sensor node receives all the information on environmental conditions (e.g., temperature, humidity, etc.) and transfers the information to the mobile operator eNB (Evolved Node B) using the User Datagram Protocol (UDP) or Transmission Control Protocol (TCP) with higher overhead. All the NB-IoT signals are managed within the mobile network operator premises by using various protocols (e.g., radio resource controls (RRC), non-access stratum (NAS), and mobility management entity (MME)). The received data are forwarded through a packet gateway (PGW) to an IoT platform that manages the cloud application. With regard to the application level, there are several options such as MQTT or CoAP. Figure 1: NB-IoT system overview with an exemplary protocol stack. Energy efficiency [10] is crucial for all the low-power IoT and M2M communication technologies including the NB-IoT. Long battery life is fundamental to extending the system life to the final goal of 10 years. A decrease in service and maintenance costs can also be achieved. Cellular technologies do not feature low power and energy efficiency by default. The NB-IoT uses LTE cellular technologies with some modifications and simplifications in order to decrease power consumption. The list of NB-IoT characteristics and assumptions is provided below:  
* Infrequent data transmissions;
* Low data rates;
* Specific dataflow;
* Extended coverage (due to the 20 dB boost of maximum losses);
* Battery and system lifetime extension by low-power device design;
* Reduced signaling compared to 'conventional' cellular technologies;
* High scalability. [PERSON] et al. [11] provided more technical details and explanations on potential NB-IoT configurations and the data exchange procedures (both uplink and downlink). [PERSON] et al. [12] explained the specific non-IP and IP-based data flow in the NB-IoT networks. Most of the early warning systems and decision support and forecasting systems for grapevine diseases currently use the well-established communication technologies such as SMS or GPRS but some alternative solutions with LoRaWAN or the NB-IoT were recently developed (e.g., Metos [13]). Where a large number of sensor devices are needed to monitor a particular area, the operation of these devices with minimum maintenance requirements should be provided. In this regard, we applied energy-saving techniques to ensure uninterrupted operation over a long time without having to recharge or replace batteries. A photovoltaic cell and a LiPo battery with a charging circuit were added to complement the usual NB-IoT power preserving methods such as the power saving mode (PSM) and the microcontroller unit sleep mode during periods of inactivity. The used energy harvesting feature enables the compensation of energy discharged by measure-and-transmit cycles, which was confirmed by measurements and calculations, as discussed in Section 2.3.