National Engineering School of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.
Fakultät für Informatik und Mathematik, University of Passau, Passau 94032, Germany.
Sensors (Basel). 2020 May 12;20(10):2760. doi: 10.3390/s20102760.
Internet of things (IoT) for precision agriculture or Smart Farming (SF) is an emerging area of application. It consists essentially of deploying wireless networks of IP-enabled sensor nodes in a partitioned farmland area. When the surface, diversity, and complexity of the farm increases, the number of sensing nodes increases, generating heavy exchange of data and messages, and thus leading to network congestion, radio interference, and high energy consumption. In this work, we propose a novel routing algorithm extending the well known IPv6 Routing Protocol for Low power and Lossy Networks (RPL). It is referred to as the Partition Aware-RPL (PA-RPL). that improves the standard IoT routing algorithm (i.e., RPL). In contrast to RPL, the proposed technique builds a routing topology enabling efficient in-network data aggregation, hence dramatically reducing data traffic through the network. Performance analysis of a typical/realistic precision agriculture case, considering the potato pest prevention from the well-known late blight disease, shows that PA-RPL improves energy saving up to 40 % , compared to standard RPL.
物联网(IoT)在精准农业或智能农业(SF)中的应用是一个新兴领域。它主要由在分区农田中部署支持 IP 的无线传感器网络节点组成。当农田的表面、多样性和复杂性增加时,传感节点的数量增加,导致大量的数据和消息交换,从而导致网络拥塞、无线电干扰和高能耗。在这项工作中,我们提出了一种新的路由算法,扩展了著名的用于低功耗和有损网络的 IPv6 路由协议(RPL)。它被称为分区感知 RPL(PA-RPL)。它改进了标准的物联网路由算法(即 RPL)。与 RPL 相比,所提出的技术构建了一种路由拓扑,能够实现有效的网络内数据聚合,从而通过网络大大减少数据流量。通过考虑著名的晚疫病防治马铃薯病虫害的典型/现实精准农业案例进行的性能分析表明,与标准 RPL 相比,PA-RPL 可将节能提高多达 40%。