UAV Routing Protocol (URP) pour la gestion de la santé des cultures

Wireless sensor networks are now a credible means for crop data collection. The installation of a fixed communication structure to relay the monitored data from the cluster head to its final destination can either be impractical because of land topology or prohibitive due to high initial cost. A plausible solution is to use Unmanned Aerial Vehicles (UAV) as an alternative means for both data collection and limited supervisory control of sensors status. In this paper, we consider the case of disjoint farming parcels each including clusters of sensors, organized in a predetermined way according to farming objectives. This research focuses to drive an optimal solution for UAV search and data gathering from all sensors installed in a crop field. Furthermore, the sensor routing protocol will take into account a tradeoff between energy management and data dissemination overhead.The proposed system is evaluated by using a simulated model and it should find out a class among all under consideration.Les réseaux de capteurs sans fil sont maintenant un moyen crédible de collecte de données sur les cultures. L'installation d'une structure de communication fixe pour relayer les données surveillées depuis la tête de grappe jusqu'à sa destination finale peut être soit impraticable en raison de la topologie du terrain, soit prohibitive en raison du coût initial élevé. Une solution plausible consiste à utiliser des véhicules aériens sans pilote (UAV) comme moyen alternatif de collecte de données et de contrôle de supervision limité de l'état des détecteurs. Dans cet article, nous considérons le cas des parcelles agricoles disjointes comprenant chacune des grappes de capteurs, organisées de manière prédéterminée en fonction des objectifs d'élevage. Cette recherche vise à trouver une solution optimale pour la recherche de UAV et la collecte de données à partir de tous les capteurs installés dans un champ de culture. En outre, le protocole de routage des capteurs tiendra compte d'un compromis entre la gestion de l'énergie et les frais généraux de diffusion des données. Le système proposé est évalué en utilisant un modèle simulé et il devrait trouver une classe parmi toutes les sous-considérations

A Hybrid Approach for the Detection and Classification of Tomato Leaf Diseases

In this paper, we proposed a hybrid deep learning approach for detecting and classifying tomato plant leaf diseases early. This hybrid system is a combination of a convolutional neural network (CNN), convolutional attention module (CBAM), and support vector machines (SVM). Initially, the proposed model can detect nine different tomato diseases but is not limited to this. The proposed system is tested using a database containing images of tomato leaves. The obtained results were very encouraging, giving us accuracy up to 97.2%, which can be improved with the improvement of learning processes. The proposed system is very efficient and lightweight, so the farmer can install it on any smart device having a digital camera and processing capabilities. With a bit of training, a farmer can detect any disease immediately, which will help him take timely pre-emptive action

Effects of Atmospheric Turbulence on Optical Wireless Communication in NEOM Smart City

International audienceThe foundation of any smart city requires an innovative and robust communication infrastructure. Many research communities envision free-space optical communication (FSO) as a promising backbone technology for the services and applications provided by such cities. However, the channel through which the FSO signal travels is the atmosphere. Therefore, the FSO performance is limited by the local weather conditions. The variation in meteorological variables leads to variations of the refractive index along the transmission path. These index inhomogeneities (i.e., atmospheric turbulence) can significantly degrade the performance of FSO systems. Thus, a practical implementation of the FSO link must carefully consider the atmospheric turbulence effect. This paper aims to investigate the feasibility of FSO communication for NEOM, a promising smart city in Saudi Arabia. We study the effect of weather conditions on FSO links using the micrometeorology model, taking into account actual weather data. The FSO performance in winter and summer was compared in terms of the bit error rate, signal-to-noise ratio (SNR), link availability, and transmission distance. The study shows that the atmospheric turbulence strength is moderate and strong in winter and summer, respectively. The temperature has the biggest impact on the FSO system when compared to the other meteorological elements included in this study. Furthermore, at transmission distances less than 300 m, atmospheric turbulence does not significantly affect the FSO for the operating wavelength of 1550 nm. Furthermore, it has been shown that at transmission distances greater than 300 m, the SNR in summer is more than 18% higher than in winter. The findings of this research enable understanding of the effect of turbulence caused by NEOM weather on the FSO link, thus assisting engineers in establishing a reliable FSO backbone link by adjusting the relevant parameters

A hybrid data collection scheme to achieve load balancing for underwater sensor networks

Underwater wireless sensor networks possess considerable potential to monitor large and hostile underwater environments by reliably sensing, collecting, and forwarding data toward the surface sinks. Although the research community has made promising efforts, barriers such as continuous node mobility, longer delays, unavailability of location information, and energy limitations must be addressed. Taking this into account, this research aims to develop a hybrid and intelligent data collection scheme that considers node position and network characteristics during data forwarding. To accomplish the objective, the network is divided into two layers. The top layer, considered more dynamic, follows a hop-by-hop data forwarding scheme. The lower layer, experiencing stable water currents, follows a clustering-based data collection method. The proposed scheme, called Multilayer Dynamic Data Forwarding (MD2F), is suitable for large and deep underwater areas. MD2F is scalable as it uses a multi-sink architecture, while single or multiple autonomous underwater vehicles (AUVs) can be utilized depending on the area being monitored. Implementing hop-by-hop transmission and clustering-based data collection at different layers balances the network load, thereby increasing the network life. Results show that MD2F exhibits better performance when compared with Multilayer Cluster-based Energy Efficient (MLCEE) and Energy efficient and link reliable routing (E2LR) schemes, both are very close in working behavior. The results are encouraging in terms of delivery ratio, network throughput, and end-to-end delays. Alongside achieving these targets, the network also exhibits less energy consumption through load balancing

Wireless Sensor’s Civil Applications, Prototypes, and Future Integration Possibilities: A Review

International audienceAdvances in wireless communication are forging new possibilities for sensors. New sensors are equipping major systems around us with unparalleled intelligence as in the case of smart grids, smart homes, and driverless vehicles. Considering the current developments in the field of sensor networks, one feels that it has reached an interesting stage, where the role of the sensors becoming crucial in numerous applications. This all speaks volumes of the fact that sensors are going to be at the front and center of most of future technologies, needless to say the Internet of Things. Considering their vital role from futuristic perspective this survey reports variety of sensors along with their characteristics and applications, which impact human life and well-being. In addition, this survey considers recent prototypes, leading sensor manufacturers as well as major projects that have made use of sensors since the last decade. Moreover, significance of this effort is that integration possibilities of sensors with other networks and major technologies are discussed, while possible challenges and key benefits are highlighted. This research effort focuses the latest developments in the area of sensors and sensor networks as research gears up to meet the challenges of the emerging technologies and their applications particularly those that emphasize smart sensors

UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use

Security Protocols in Drones: Issues and Challenges

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Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk

International audienceDespite the perception people may have regarding the agricultural process, the reality is that today's agriculture industry is data-centered, precise, and smarter than ever. The rapid emergence of the Internet-of-Things (IoT) based technologies redesigned almost every industry including “smart agriculture” which moved the industry from statistical to quantitative approaches. Such revolutionary changes are shaking the existing agriculture methods and creating new opportunities along a range of challenges. This article highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges expected to be faced when integrating this technology with the traditional farming practices. IoT devices and communication techniques associated with wireless sensors encountered in agriculture applications are analyzed in detail. What sensors are available for specific agriculture application, like soil preparation, crop status, irrigation, insect and pest detection are listed. How this technology helping the growers throughout the crop stages, from sowing until harvesting, packing and transportation is explained. Furthermore, the use of unmanned aerial vehicles for crop surveillance and other favorable applications such as optimizing crop yield is considered in this article. State-of-the-art IoT-based architectures and platforms used in agriculture are also highlighted wherever suitable. Finally, based on this thorough review, we identify current and future trends of IoT in agriculture and highlight potential research challenges

Direction of Arrival of Narrowband Signals Based on Virtual Phased Antennas

International audienceData collection from field sensors by using Unmanned Aerial Vehicle (UAV) is the application taken in consideration in this paper. All the sensor nodes are kept location unaware to reduce their cost and energy utilization. The issue addressed in this paper is localization of sensor nodes by UAV to collect data in efficient way. ULA of multiple antennas are used to measure the Angle of Arrival (AoA) of incoming signals. However, the drawbacks of mounting such multiple antennas on an Unmanned Aerial Vehicle (UAV) outweigh the benefits. The challenge is to affix multiple antennas and receivers on an UAV, increase its weight which ultimately decrease its payload capacity, flight time, speed and agility. In this paper, we are proposing a new method to estimate the AoA, called Virtual Phase Array (VPA) antenna system. A single moving antenna installed over an UAV taking snapshots every fixed time periods forms an antenna array virtually. This VPA has enable us to introduce two new concepts of adaptive staring precision and multiple frequency use. All these became reality only because number and spacing between antenna elements can be adjusted, which is not easy to implement in physical antenna array especially when antenna is onboard. The proposed system is evaluated by simulation model. Suggested modifications and additions in classical MUSIC algorithm make it possible to operate the virtual antenna system with the same precision as the physical antenna may have, but adding more flexibility, ease of use, cost economy, more reliability and better throughput