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Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite and climate data, this research aims to enhance the accuracy and resolution of soil moisture estimation, enabling more effective agricultural planning, irrigation management, and environmental monitoring. Five ML models, including linear regression, support vector machines, decision trees, random forests, and long short-term memory networks (LSTM), are evaluated and compared using real-world data from multiple geographical regions, which includes a dataset from NASA's SMAP project, supplemented by climate data, which employs both active and passive sensors for data collection. The outcomes demonstrate that the LSTM model consistently outperforms other ML algorithms across various evaluation metrics, highlighting the effectiveness of WSN-driven approaches to soil moisture estimation. The study contributes to the advancement of soil moisture monitoring technologies, offering insights into the potential of WSNs combined with ML and DL for sustainable agriculture and environmental management practices. [ABSTRACT FROM AUTHOR]

There are two common approaches to design a time synchronization protocol as reference-based and consensus-based. The first approach is mainly employed in protocols operating in large-scale wireless sensor networks (WSNs) because of its fast convergence. However, reference-based time synchronization protocols are vulnerable to node-failure in real-world applications. Although consensus-based time synchronization protocols do not experience the aforementioned problem, they are not suitable for operation in large-scale WSNs owing to their slow convergence. In this study, we propose a hybrid time synchronization protocol (HTSP) to utilize the advantages of both approaches. In particular, HTSP exploits a temporary reference node to significantly reduce the convergence time and employs average-based consensus during normal operation to cope with node failures. It is notable that each node in HTSP can seamlessly switch between the reference and consensus modes during its operation. Moreover, HTSP is a fully distributed protocol as it does not rely on any leader-election mechanism. Our simulation results demonstrated that HTSP outperforms flooding, gradient, and virtual link-based time synchronization protocols considering various types of network topologies and scales. [ABSTRACT FROM AUTHOR]

Among the flooding-based time synchronization protocols in wireless sensor networks, rapid-flooding outperforms slow-flooding in terms of synchronization speed. However, sometimes it is not realistic to apply rapid-flooding in dense or low-duty cycle networks due to its operational constraint that timing messages must be forwarded immediately after being received. On the contrary, slow-flooding protocols are free from this operational constraint, but they have a fundamental limitation that their convergence time increases with the size of the network. In this letter, we prove that this limitation can be overcome by sharing the compensated skew and timing information to the next hop nodes so that they can all be synchronized in the same round. The evaluation results demonstrate that we can achieve a comparable convergence speed of rapid-flooding protocols with the slow-flooding-based mechanism and can provide better accuracy for network-wide and per-hop synchronization. [ABSTRACT FROM AUTHOR]

The Internet of Things will enable objects to be identified, sensed, and controlled remotely across the existing Internet infrastructure. Even though interacting with sensor nodes requires a priori knowledge about the application profile implemented on the desired nodes, it is infeasible for user applications to have any information in advance or to obtain such information from resource-constrained sensor nodes. In this paper, we propose a scalable and efficient metadata framework that allows user applications to learn all about sensor nodes at runtime without storing heavy descriptive data within the nodes themselves. In this framework, every sensor node has globally unique identifiers, and their metadata describing functions and capabilities are stored in distributed metadata servers. To enable metadata retrieval from the globally unique identifier of sensor nodes, we exploit a hierarchical resolution server architecture defined in global standards. We prove the feasibility as well as scalability and efficiency of the proposed framework by evaluating the metadata retrieval overhead from a ZigBee based testbed. [ABSTRACT FROM AUTHOR]

The ZigBee tree routing is widely used in many resource-limited devices and applications, since it does not require any routing table and route discovery overhead to send a packet to the destination. However, the ZigBee tree routing has the fundamental limitation that a packet follows the tree topology; thus, it cannot provide the optimal routing path. In this paper, we propose the shortcut tree routing (STR) protocol that provides the near optimal routing path as well as maintains the advantages of the ZigBee tree routing such as no route discovery overhead and low memory consumption. The main idea of the shortcut tree routing is to calculate remaining hops from an arbitrary source to the destination using the hierarchical addressing scheme in ZigBee, and each source or intermediate node forwards a packet to the neighbor node with the smallest remaining hops in its neighbor table. The shortcut tree routing is fully distributed and compatible with ZigBee standard in that it only utilizes addressing scheme and neighbor table without any changes of the specification. The mathematical analysis proves that the 1-hop neighbor information improves overall network performances by providing an efficient routing path and distributing the traffic load concentrated on the tree links. In the performance evaluation, we show that the shortcut tree routing achieves the comparable performance to AODV with limited overhead of neighbor table maintenance as well as overwhelms the ZigBee tree routing in all the network conditions such as network density, network configurations, traffic type, and the network traffic. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in the special issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs. [ABSTRACT FROM AUTHOR]

The time synchronization protocol is indispensable in various applications of wireless sensor networks, such as scheduling, monitoring, and tracking. Numerous protocols and algorithms have been proposed in recent decades, and many of them provide micro-scale resolutions. However, designing and implementing a time synchronization protocol in a practical wireless network is very challenging compared to implementation in a wired network; this is because its performance can be deteriorated significantly by many factors, including hardware quality, message delay jitter, ambient environment, and network topology. In this study, we measure the performance of the Flooding Time Synchronization Protocol (FTSP) and Gradient Time Synchronization Protocol (GTSP) in terms of practical network conditions, such as message delay jitter, synchronization period, network topology, and packet loss. This study provides insights into the operation and optimization of time synchronization protocols. In addition, the performance evaluation identifies that FTSP is highly affected by message delay jitter due to error accumulation over multi-hops. We demonstrate that the proposed extended version of the FTSP (E-FTSP) alleviates the effect of message delay jitter and enhances the overall performance of FTSP in terms of error, time, and other factors. [ABSTRACT FROM AUTHOR]