# Precision Agriculture: A Remote Sensing Monitoring System Architecture +
## 4 The Network Layer
### The Encapsulation Layer  
Most of the current agro-environmental monitoring applications are based on machine to machine (M2M) communication support regarding real-time data transmission. There is a variety of communication patterns to be used so that the terminal can receive the information necessary to monitor the production. WSN technologies, enhanced by the IoT paradigm, enable smart sensor communication and connection to the IPv6-based internet, by addressing the agricultural sensors with IPv6 long addresses that can fit in lightweight IoT data link frames. IoT can immensely improve the autonomous capabilities of resourced-constrained nodes in a Low-power and Lossy Network (LLN). An agricultural WSN is a LLN. In such a network, some of the nodes may have a direct Internet connection to send and receive messages from the Internet. However, other nodes from the same network, may lack that kind of ability due to hardware limitations, and require the use of the Internet-connected nodes to access external services. Data exchange in a local context is also possible without the necessity of transmitting data to the Internet. The task of discovering the routes and allowing data messages to be transmitted among agricultural sensor nodes is performed by the routing protocol. Due to this fact, in such networks, network performance is strongly related to how the routing protocols use the limited hardware resources of the network device. * The 6 LoWPAN [7; 26] is the most popular network encapsulation protocol for precision agriculture applications. It refers to the transmission of IPv6 protocol packets over Low-Power Wireless \begin{table}
\begin{tabular}{c c c} \hline \hline
**Routing Protocols** & **Category** & **Features** \\ \hline Destination-Sequenced & & Route availability to all network destinations with minimal delay. \\ \hline Link Estimation Parent & & A map of the network is kept regarding the interconnection of nodes. \\ \hline Tiny Lightweight UNderlay & & Provided interfaces help to form route characteristics. \\ \hline Ad-hoc On-Demand & & Used in ZigBee communication protocol for interconnection of sensor nodes. \\ Distance Vector(ADDV) & & Reactive \\ \hline Dynamic Source & & A route on demand is formed when a transmission node requests it. \\ Routing(DSR) & & \\ \hline Optimized Link State & & Information about the status of the nodes is used to select the appropriate path for packet forwarding. \\ Routing Protocol (OLSR) & & Reliable retransmission of information using confirmation messages. \\ \hline ProtoSense & & \\ \hline Periodic Threshold-Sensitive & & \\ Energy-Efficient Sensor & & It takes into account energy saving and network lifetime [24]. \\ Network (APTEEN) & & \\ \hline Location Routing Algorithm & & It uses the flood method in a hierarchical network structure to route data packets. \\ with Cluster-Based Flooding & & \\ (LORA-CBF) [25] & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Smart farming routing protocols. Personal Area Networks. In a smart farming monitoring system, it is used by sensor devices that are compatible with the IEEE802.15.4 standard for WSNs. 6 LoWPAN efficiently encapsulates IPv6 long headers in IEEE 802.15.4 small data frames for information exchange between sensor nodes. The advantages of this protocol are that it uses a special header compression method and a fragmentation process to reduce the transmission overhead [10]. * The IPv6 over LoRa [27] implementation enables the transmission of IPv6 protocol packets over LoRa links. If LoRaWAN is chosen for sensor node communication in a smart farming monitoring system, LoRa is the MAC protocol responsible for establishing communication between the LoRa gateway and the LoRa sensor end devices. In an agriculture monitoring system, the IPv6 adaptation enables the deployment of the IoT paradigm as a separate architectural layer. The basic aim of this layer is to manage header compression and packet fragmentation to deal with the requirements of LoRa modulation in the physical layer.