Ground Wireless Sensor Network Research Articles

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

Unmanned Aerial Vehicles (UAVs) have been widely applied for pesticide spraying as they have high efficiency and operational flexibility. However, the pesticide droplet drift caused by wind may decrease the pesticide spraying efficiency and pollute the environment. A precision spraying system based on an airborne meteorological monitoring platform on manned agricultural aircrafts is not adaptable for. So far, there is no better solution for controlling droplet drift outside the target area caused by wind, especially by wind gusts. In this regard, a UAV trajectory adjustment system based on Wireless Sensor Network (WSN) for pesticide drift control was proposed in this research. By collecting data from ground WSN, the UAV utilizes the wind speed and wind direction as inputs to autonomously adjust its trajectory for keeping droplet deposition in the target spraying area. Two optimized algorithms, namely deep reinforcement learning and particle swarm optimization, were applied to generate the newly modified flight route. At the same time, a simplified pesticide droplet drift model that includes wind speed and wind direction as parameters was developed and adopted to simulate and compute the drift distance of pesticide droplets. Moreover, an LSTM-based wind speed prediction model and a RNN-based wind direction prediction model were established, so as to address the problem of missing the latest wind data caused by communication latency or a lack of connection with the ground nodes. Finally, experiments were carried out to test the communication latency between UAV and ground WSN, and to evaluate the proposed scheme with embedded Raspberry Pi boards in UAV for feasibility verification. Results show that the WSN-assisted UAV trajectory adjustment system is capable of providing a better performance of on-target droplet deposition for real time pesticide spraying with UAV.

Advanced UAV-WSN System for Intelligent Monitoring in Precision Agriculture.

The growing need for food worldwide requires the development of a high-performance, high-productivity, and sustainable agriculture, which implies the introduction of new technologies into monitoring activities related to control and decision-making. In this regard, this paper presents a hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture. The integration of UAVs with intelligent, ground WSNs, and IoT proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications. Key advantages lay in online data collection and relaying to a central monitoring point, while effectively managing network load and latency through optimized UAV trajectories and in situ data processing. Two important aspects of the collaboration were considered: designing the UAV trajectories for efficient data collection and implementing effective data processing algorithms (consensus and symbolic aggregate approximation) at the network level for the transmission of the relevant data. The experiments were carried out at a Romanian research institute where different crops and methods are developed. The results demonstrate that the collaborative UAV–WSN–IoT approach increases the performances in both precision agriculture and ecological agriculture.

Development of Radio-Frequency Sensor Wake-Up with Unmanned Aerial Vehicles as an Aerial Gateway.

The advent of autonomous navigation, positioning, and general robotics technologies has enabled the improvement of small to miniature-sized unmanned aerial vehicles (UAVs, or ‘drones’) and their wide uses in engineering practice. Recent research endeavors further envision a systematic integration of aerial drones and traditional contact-based or ground-based sensors, leading to an aerial–ground wireless sensor network (AG-WSN), in which the UAV serves as both a gateway besides and a remote sensing platform. This paper serves two goals. First, we will review the recent development in architecture, design, and algorithms related to UAVs as a gateway and particularly illustrate its nature in realizing an opportunistic sensing network. Second, recognizing the opportunistic sensing need, we further aim to focus on achieving energy efficiency through developing an active radio frequency (RF)-based wake-up mechanism for aerial–ground data transmission. To prove the effectiveness of energy efficiency, several sensor wake-up solutions are physically implemented and evaluated. The results show that the RF-based wake-up mechanism can potentially save more than 98.4% of the energy that the traditional duty-cycle method would otherwise consume, and 96.8% if an infrared-receiver method is used.

Evaluation and Improvement of SMOS and SMAP Soil Moisture Products for Soils with High Organic Matter over a Forested Area in Northeast China

Soil moisture (SM) retrieval from SMOS (the Soil Moisture and Ocean Salinity mission) and SMAP (the Soil Moisture Active/Passive mission) passive microwave data over forested areas with required accuracy is of great significance and poses some challenges. In this paper, we used Ground Wireless Sensor Network (GWSN) SM measurements from 9 September to 5 November 2015 to validate SMOS and SMAP Level 3 (L3) SM products over forested areas in northeastern China. Our results found that neither SMOS nor SMAP L3 SM products were ideal, with respective RMSE (root mean square error) values of 0.31 cm3/cm3 and 0.17 cm3/cm3. Nevertheless, some improvements in SM retrieval might be achievable through refinements of the soil dielectric model with respect to high percentage of soil organic matter (SOM) in the forested area. To that end, the potential of the semi-empirical soil dielectric model proposed by Jun Liu (Liu’s model) in improving SM retrieval results over forested areas was investigated. Introducing Liu’s model into the retrieval algorithms of both SMOS and SMAP missions produced promising results. For SMAP, the RMSE of L3 SM products improved from 0.16 cm3/cm3 to 0.07 cm3/cm3 for AM (local solar time around 06:00 am) data, and from 0.17 cm3/cm3 to 0.05 cm3/cm3 for PM (local solar time around 06:00 pm) data. For SMOS ascending orbit products, the accuracy was improved by 56%, while descending orbit products improved by 45%.

An optimization method to improve the performance of unmanned aerial vehicle wireless sensor networks

Wireless sensor networks have made great progress in recent years in every aspect of our life. To extend their range of application and provide a further effective option for remote surveillance, unmanned aerial vehicles have been gradually introduced into sensor networks, due to their advantages of flexibility, mobility, and ease of realization. Despite the success of various applications and studies in this new field, unmanned aerial vehicle–wireless sensor network still faces many open challenges, such as the unmanned aerial vehicle capable system framework, land-wireless sensor network management, and unmanned aerial vehicle mission planning strategies. In the article, we propose a cooperative framework for unmanned aerial vehicle–wireless sensor network, which is composed of sensor nodes, fixed-group leaders, and a unmanned aerial vehicle-Sink, in which a three-layer hierarchical network is formed. A land-wireless sensor network k-means driven grouping approach is then presented, which considers the communication performance, the position, and other factors. Additionally, a simulated annealing algorithm is employed to detect the optimal flight trajectory according the ground wireless sensor network architecture. Finally, the proposed approach is compared to other related approaches, and the results have shown better performance of our proposal in terms of energy consumption, flying time, and other relevant evaluation criteria.

A Dynamic Time-slot Assignment for Ground Wireless Sensor Network

This paper is on the background of the applied communications of automated vehicle in the multi-hop environment. The paper provides a dynamic time-slot assignment protocol for the ground wireless sensor network (WSN), based on TDMA. By interacting of the two-hop neighboring nodes information, the protocol finishes the dynamic time-slot assignment, realizes the efficient and fair sharing of channel, reduces the transfer delay of the end-to-end burst data, meets the communication demand of assignment on-demand in WSN, and prolongs the life-time of the network with the virtual backbone mechanism. The theoretical analysis and simulation results showed that the protocol provided has better adaptability for the burst network services and topological variation, comparing to the traditional static mac layer protocol in the TDMA system. multiple address (TDMA), automated vehicle 1. Background WSN has widely used in various fields, especially in the military field. It is well suited to use in the wretched battlefield environment, including monitoring our forces, materials and equipment, keeping watch over the conflict zones, detecting the topography and defensive of the enemy, aiming the targets, assessing the damage, detecting the nuclear, biological and chemical attacks. WSN on the ground is disposed into three parts: the lowest part is the smallest and lowest power consumption attended sensor, the second part is the directional sensor which could assess the azimuth and the third part is the confirmed sensor which has a imaging ability. The first two parts only need slow communications (kbps) between each other and the communication distance is 100-400 meters. The confirmed sensor in the third part need two-speed or two transceivers (Mbps), the one is responsible for the communication with the lower node and the other one is responsible for the communication with the directorial node in a distance which could not exceed 10km. Based on the communication of the ground sensor by using unmanned vehicle in mobile multi-hop, a MAC protocols for the ground wireless network is designed, a TDMA-based dynamic TSA protocol is proposed, this protocol can complete the TSA process by the communication between two neighboring nodes, which can realize the sharing of the high-quality and fair-minded signal path, fulfilling the demand to distribute the communication according to need for the ground wireless network at the same time. This review is followed by an introduction. A brief summary of some of the relevant concepts is presented in Section 2.Section 3 demonstrates the protocol design. Section 4 is the theoretical performance study of the protocol. In Section 5, we discuss the preliminary results of a simulation study. Finally, conclusions and future work are summarized.

VHF communication channel characterisations over complex wooded propagation paths with applications to ground wireless sensor networks

Results of measurement trials to estimate path loss and signal fading levels in very-high frequency band are presented for a node-to-node ad-hoc sensor network communication link with very low elevated antennas. Different typical landscapes were tested; from flat open areas to uneven woodland areas. Practical recommendations regarding utilisation of VHF band are formulated.

Real Time Relative and Absolute Dynamic Localization of Air–Ground Wireless Sensor Networks

A novel approach for relative and absolute localization of wireless sensor nodes using a potential field method is presented. The main idea of our work is to develop relative and absolute localization algorithms for the position estimate of stationary unattended ground sensor (UGS) nodes using a potential field method. A dynamical model is derived for each sensor node to estimate the relative and absolute position estimates under the influence of a certain fictitious virtual force. In the algorithm the sensor nodes do not move physically, but a virtual motion is carried out to generate optimal position estimates. The convergence of the estimator system to a least squares solution is guaranteed using Lyapunov theory. Separate control algorithms for relative and absolute localization are developed which guarantee the convergence of the position estimates. The relative localization algorithm assumes that distance (i.e. range) measurements between UGS nodes are available and for absolute localization algorithm, uninhabited aerial vehicles (UAV) are available with on board GPS such that they have absolute position information together with range measurement information. In the relative localization algorithm the UGS nodes are localized with respect to an internal co-ordinate frame. In absolute localization the UGS nodes are localized with respect to the known absolute position of UAV in the air---ground network. The effectiveness of the control algorithm is highlighted by the real time implementation results.