Development of a GIS-based method for sensor network deployment and coverage optimization

Au cours des dernières années, les réseaux de capteurs ont été de plus en plus utilisés dans différents contextes d’application allant de la surveillance de l’environnement au suivi des objets en mouvement, au développement des villes intelligentes et aux systèmes de transport intelligent, etc. Un réseau de capteurs est généralement constitué de nombreux dispositifs sans fil déployés dans une région d'intérêt. Une question fondamentale dans un réseau de capteurs est l'optimisation de sa couverture spatiale. La complexité de l'environnement de détection avec la présence de divers obstacles empêche la couverture optimale de plusieurs zones. Par conséquent, la position du capteur affecte la façon dont une région est couverte ainsi que le coût de construction du réseau. Pour un déploiement efficace d'un réseau de capteurs, plusieurs algorithmes d'optimisation ont été développés et appliqués au cours des dernières années. La plupart de ces algorithmes reposent souvent sur des modèles de capteurs et de réseaux simplifiés. En outre, ils ne considèrent pas certaines informations spatiales de l'environnement comme les modèles numériques de terrain, les infrastructures construites humaines et la présence de divers obstacles dans le processus d'optimisation. L'objectif global de cette thèse est d'améliorer les processus de déploiement des capteurs en intégrant des informations et des connaissances géospatiales dans les algorithmes d'optimisation. Pour ce faire, trois objectifs spécifiques sont définis. Tout d'abord, un cadre conceptuel est développé pour l'intégration de l'information contextuelle dans les processus de déploiement des réseaux de capteurs. Ensuite, sur la base du cadre proposé, un algorithme d'optimisation sensible au contexte local est développé. L'approche élargie est un algorithme local générique pour le déploiement du capteur qui a la capacité de prendre en considération de l'information spatiale, temporelle et thématique dans différents contextes d'applications. Ensuite, l'analyse de l'évaluation de la précision et de la propagation d'erreurs est effectuée afin de déterminer l'impact de l'exactitude des informations contextuelles sur la méthode d'optimisation du réseau de capteurs proposée. Dans cette thèse, l'information contextuelle a été intégrée aux méthodes d'optimisation locales pour le déploiement de réseaux de capteurs. L'algorithme développé est basé sur le diagramme de Voronoï pour la modélisation et la représentation de la structure géométrique des réseaux de capteurs. Dans l'approche proposée, les capteurs change leur emplacement en fonction des informations contextuelles locales (l'environnement physique, les informations de réseau et les caractéristiques des capteurs) visant à améliorer la couverture du réseau. La méthode proposée est implémentée dans MATLAB et est testée avec plusieurs jeux de données obtenus à partir des bases de données spatiales de la ville de Québec. Les résultats obtenus à partir de différentes études de cas montrent l'efficacité de notre approche.In recent years, sensor networks have been increasingly used for different applications ranging from environmental monitoring, tracking of moving objects, development of smart cities and smart transportation system, etc. A sensor network usually consists of numerous wireless devices deployed in a region of interest. A fundamental issue in a sensor network is the optimization of its spatial coverage. The complexity of the sensing environment with the presence of diverse obstacles results in several uncovered areas. Consequently, sensor placement affects how well a region is covered by sensors as well as the cost for constructing the network. For efficient deployment of a sensor network, several optimization algorithms are developed and applied in recent years. Most of these algorithms often rely on oversimplified sensor and network models. In addition, they do not consider spatial environmental information such as terrain models, human built infrastructures, and the presence of diverse obstacles in the optimization process. The global objective of this thesis is to improve sensor deployment processes by integrating geospatial information and knowledge in optimization algorithms. To achieve this objective three specific objectives are defined. First, a conceptual framework is developed for the integration of contextual information in sensor network deployment processes. Then, a local context-aware optimization algorithm is developed based on the proposed framework. The extended approach is a generic local algorithm for sensor deployment, which accepts spatial, temporal, and thematic contextual information in different situations. Next, an accuracy assessment and error propagation analysis is conducted to determine the impact of the accuracy of contextual information on the proposed sensor network optimization method. In this thesis, the contextual information has been integrated in to the local optimization methods for sensor network deployment. The extended algorithm is developed based on point Voronoi diagram in order to represent geometrical structure of sensor networks. In the proposed approach sensors change their location based on local contextual information (physical environment, network information and sensor characteristics) aiming to enhance the network coverage. The proposed method is implemented in MATLAB and tested with several data sets obtained from Quebec City spatial database. Obtained results from different case studies show the effectiveness of our approach

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Dense and long-term monitoring of Earth surface processes with passive RFID -- a review

Billions of Radio-Frequency Identification (RFID) passive tags are produced yearly to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing to monitor earth surface processes. Indeed, passive tags can cost 10 to 100 times less than wireless sensors networks and require little maintenance, facilitating years-long monitoring with ten's to thousands of tags. This study reviews the existing and potential applications of RFID in geosciences. The most mature application today is the study of coarse sediment transport in rivers or coastal environments, using tags placed into pebbles. More recently, tag localization was used to monitor landslide displacement, with a centimetric accuracy. Sensing tags were used to detect a displacement threshold on unstable rocks, to monitor the soil moisture or temperature, and to monitor the snowpack temperature and snow water equivalent. RFID sensors, available today, could monitor other parameters, such as the vibration of structures, the tilt of unstable boulders, the strain of a material, or the salinity of water. Key challenges for using RFID monitoring more broadly in geosciences include the use of ground and aerial vehicles to collect data or localize tags, the increase in reading range and duration, the ability to use tags placed under ground, snow, water or vegetation, and the optimization of economical and environmental cost. As a pattern, passive RFID could fill a gap between wireless sensor networks and manual measurements, to collect data efficiently over large areas, during several years, at high spatial density and moderate cost.Comment: Invited paper for Earth Science Reviews. 50 pages without references. 31 figures. 8 table

DronAway: A Proposal on the Use of Remote Sensing Drones as Mobile Gateway for WSN in Precision Agriculture

[EN] The increase in the world population has led to new needs for food. Precision Agriculture (PA) is one of the focuses of these policies to optimize the crops and facilitate crop management using technology. Drones have been gaining popularity in PA to perform remote sensing activities such as photo and video capture as well as other activities such as fertilization or scaring animals. These drones could be used as a mobile gateway as well, benefiting from its already designed flight plan. In this paper, we evaluate the adequacy of remote sensing drones to perform gateway functionalities, providing a guide for choosing the best drone parameters for successful WiFi data transmission between sensor nodes and the gateway in PA systems for crop monitoring and management. The novelty of this paper compared with existing mobile gateway proposals is that we are going to test the performance of the drone that is acting as a remote sensing tool to carry a low-cost gateway node to gather the data from the nodes deployed on the field. Taking this in mind, simulations of different scenarios were performed to determine if the data can be transmitted correctly or not considering different flying parameters such as speed (from 1 to 20 m/s) and flying height (from 4 to 104 m) and wireless sensor network parameters such as node density (1 node each 60 m(2) to 1 node each 5000 m(2)) and antenna coverage (25 to 200 m). We have calculated the time that each node remains with connectivity and the time required to send the data to estimate if the connection will be bad, good, or optimal. Results point out that for the maximum node density, there is only one combination that offers good connectivity (lowest velocity, the flying height of 24 m, and antenna with 25 m of coverage). For the other node densities, several combinations of flying height and antenna coverage allows good and optimal connectivity.This work is partially founded by the European Union with the "Fondo Europeo Agricola de Desarrollo Rural (FEADER)-Europa invierte en zonas rurales", the MAPAMA, and Comunidad de Madrid with the IMIDRA, under the mark of the PDR-CM 2014-2020" project number PDR18-XEROCESPED, by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR, and by Conselleria de Educacion, Cultura y Deporte with the Subvenciones para la contratacion de personal investigador en fase postdoctoral, grant number APOSTD/2019/04.García, L.; Parra-Boronat, L.; Jimenez, JM.; Lloret, J.; Mauri, PV.; Lorenz, P. (2020). DronAway: A Proposal on the Use of Remote Sensing Drones as Mobile Gateway for WSN in Precision Agriculture. Applied Sciences. 10(19):1-23. https://doi.org/10.3390/app10196668S1231019Agriculture and Rural Development Agriculture and Rural Development https://ec.europa.eu/agriculture/cap-post-2013/Kropff, M. J., Wallinga, J., & Lotz, L. A. P. (2007). Modelling for Precision Weed Management. Ciba Foundation Symposium 210 - Precision Agriculture: Spatial and Temporal Variability of Environmental Quality, 182-207. doi:10.1002/9780470515419.ch12Toth, C., & Jóźków, G. (2016). Remote sensing platforms and sensors: A survey. ISPRS Journal of Photogrammetry and Remote Sensing, 115, 22-36. doi:10.1016/j.isprsjprs.2015.10.004Pajares, G. (2015). Overview and Current Status of Remote Sensing Applications Based on Unmanned Aerial Vehicles (UAVs). Photogrammetric Engineering & Remote Sensing, 81(4), 281-330. doi:10.14358/pers.81.4.281Maes, W. H., & Steppe, K. (2019). Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture. Trends in Plant Science, 24(2), 152-164. doi:10.1016/j.tplants.2018.11.007Psirofonia, P., Samaritakis, V., Eliopoulos, P., & Potamitis, I. (2017). Use of Unmanned Aerial Vehicles for Agricultural Applications with Emphasis on Crop Protection: Three Novel Case - studies. International Journal of Agricultural Science and Technology, 5(1), 30-39. doi:10.12783/ijast.2017.0501.03Agriculture Drones Market by Offering (Hardware and Software & Services), Application (Precision Farming, Livestock Monitoring, Precision Fish Farming, and Smart Greenhouse), Component, and Geography—Global Forecast to 2024 https://www.marketsandmarkets.com/Market-Reports/agriculture-drones-market-23709764.html?gclid=CjwKCAiA-P7xBRAvEiwAow-VaRPLzQ4x9YHOwUyC4e-PBfJvjpkB4Bqx9WWIt6S-lM0FsKvUcbqLdxoC_VcQAvD_BwECunliffe, A. M., Brazier, R. E., & Anderson, K. (2016). Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry. Remote Sensing of Environment, 183, 129-143. doi:10.1016/j.rse.2016.05.019Zhang, J., Hu, J., Lian, J., Fan, Z., Ouyang, X., & Ye, W. (2016). Seeing the forest from drones: Testing the potential of lightweight drones as a tool for long-term forest monitoring. Biological Conservation, 198, 60-69. doi:10.1016/j.biocon.2016.03.027Urbahs, A., & Jonaite, I. (2013). FEATURES OF THE USE OF UNMANNED AERIAL VEHICLES FOR AGRICULTURE APPLICATIONS. Aviation, 17(4), 170-175. doi:10.3846/16487788.2013.861224Raeva, P. L., Šedina, J., & Dlesk, A. (2018). Monitoring of crop fields using multispectral and thermal imagery from UAV. European Journal of Remote Sensing, 52(sup1), 192-201. doi:10.1080/22797254.2018.1527661Stehr, N. J. (2015). Drones: The Newest Technology for Precision Agriculture. Natural Sciences Education, 44(1), 89-91. doi:10.4195/nse2015.04.0772Kurkute, S. R. (2018). Drones for Smart Agriculture: A Technical Report. International Journal for Research in Applied Science and Engineering Technology, 6(4), 341-346. doi:10.22214/ijraset.2018.4061Puri, V., Nayyar, A., & Raja, L. (2017). Agriculture drones: A modern breakthrough in precision agriculture. Journal of Statistics and Management Systems, 20(4), 507-518. doi:10.1080/09720510.2017.1395171Valente, J., Sanz, D., Barrientos, A., Cerro, J. del, Ribeiro, Á., & Rossi, C. (2011). An Air-Ground Wireless Sensor Network for Crop Monitoring. Sensors, 11(6), 6088-6108. doi:10.3390/s110606088Hunt, E. R., & Daughtry, C. S. T. (2017). What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture? International Journal of Remote Sensing, 39(15-16), 5345-5376. doi:10.1080/01431161.2017.1410300Tsouros, D. C., Bibi, S., & Sarigiannidis, P. G. (2019). A Review on UAV-Based Applications for Precision Agriculture. Information, 10(11), 349. doi:10.3390/info10110349Daponte, P., De Vito, L., Glielmo, L., Iannelli, L., Liuzza, D., Picariello, F., & Silano, G. (2019). A review on the use of drones for precision agriculture. IOP Conference Series: Earth and Environmental Science, 275, 012022. doi:10.1088/1755-1315/275/1/012022Boehm, F., & Schulte, A. (2013). Air to ground sensor data distribution using IEEE802.11N Wi-Fi network. 2013 IEEE/AIAA 32nd Digital Avionics Systems Conference (DASC). doi:10.1109/dasc.2013.6712581Stek, T. D. (2016). Drones over Mediterranean landscapes. The potential of small UAV’s (drones) for site detection and heritage management in archaeological survey projects: A case study from Le Pianelle in the Tappino Valley, Molise (Italy). Journal of Cultural Heritage, 22, 1066-1071. doi:10.1016/j.culher.2016.06.006Marín, J., Parra, L., Rocher, J., Sendra, S., Lloret, J., Mauri, P. V., & Masaguer, A. (2018). Urban Lawn Monitoring in Smart City Environments. Journal of Sensors, 2018, 1-16. doi:10.1155/2018/8743179Ojha, T., Misra, S., & Raghuwanshi, N. S. (2015). Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges. Computers and Electronics in Agriculture, 118, 66-84. doi:10.1016/j.compag.2015.08.011Tzounis, A., Katsoulas, N., Bartzanas, T., & Kittas, C. (2017). Internet of Things in agriculture, recent advances and future challenges. Biosystems Engineering, 164, 31-48. doi:10.1016/j.biosystemseng.2017.09.007Aqeel-ur-Rehman, Abbasi, A. Z., Islam, N., & Shaikh, Z. A. (2014). A review of wireless sensors and networks’ applications in agriculture. Computer Standards & Interfaces, 36(2), 263-270. doi:10.1016/j.csi.2011.03.004Ruiz-Garcia, L., Lunadei, L., Barreiro, P., & Robla, I. (2009). A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State of the Art and Current Trends. Sensors, 9(6), 4728-4750. doi:10.3390/s90604728Srbinovska, M., Gavrovski, C., Dimcev, V., Krkoleva, A., & Borozan, V. (2015). Environmental parameters monitoring in precision agriculture using wireless sensor networks. Journal of Cleaner Production, 88, 297-307. doi:10.1016/j.jclepro.2014.04.036Yu, X., Wu, P., Han, W., & Zhang, Z. (2013). A survey on wireless sensor network infrastructure for agriculture. Computer Standards & Interfaces, 35(1), 59-64. doi:10.1016/j.csi.2012.05.001Chaudhary, D. D., Nayse, S. P., & Waghmare, L. M. (2011). Application of Wireless Sensor Networks for Greenhouse Parameter Control in Precision Agriculture. International Journal of Wireless & Mobile Networks, 3(1), 140-149. doi:10.5121/ijwmn.2011.3113Díaz, S. E., Pérez, J. C., Mateos, A. C., Marinescu, M.-C., & Guerra, B. B. (2011). A novel methodology for the monitoring of the agricultural production process based on wireless sensor networks. Computers and Electronics in Agriculture, 76(2), 252-265. doi:10.1016/j.compag.2011.02.004Zhu, Y., Song, J., & Dong, F. (2011). Applications of wireless sensor network in the agriculture environment monitoring. Procedia Engineering, 16, 608-614. doi:10.1016/j.proeng.2011.08.1131Keshtgari, M., & Deljoo, A. (2012). A Wireless Sensor Network Solution for Precision Agriculture Based on Zigbee Technology. Wireless Sensor Network, 04(01), 25-30. doi:10.4236/wsn.2012.41004Hwang, J., Shin, C., & Yoe, H. (2010). Study on an Agricultural Environment Monitoring Server System using Wireless Sensor Networks. Sensors, 10(12), 11189-11211. doi:10.3390/s101211189Garcia-Sanchez, A.-J., Garcia-Sanchez, F., & Garcia-Haro, J. (2011). Wireless sensor network deployment for integrating video-surveillance and data-monitoring in precision agriculture over distributed crops. Computers and Electronics in Agriculture, 75(2), 288-303. doi:10.1016/j.compag.2010.12.005García, L., Parra, L., Jimenez, J. M., Lloret, J., & Lorenz, P. (2019). Practical Design of a WSN to Monitor the Crop and its Irrigation System. Network Protocols and Algorithms, 10(4), 35. doi:10.5296/npa.v10i4.14147Popescu, D., Stoican, F., Stamatescu, G., Ichim, L., & Dragana, C. (2020). Advanced UAV–WSN System for Intelligent Monitoring in Precision Agriculture. Sensors, 20(3), 817. doi:10.3390/s20030817Specifications of the WEMOS MINI DI https://docs.wemos.cc/en/latest/d1/d1_mini.htmlSpecifications of the Node MCU https://joy-it.net/en/products/SBC-NodeMCU-ESP32Specifications of the Arduino Mega https://store.arduino.cc/arduino-mega-2560-rev3Specifications of the Arduino UNO https://store.arduino.cc/arduino-uno-rev3Specifications of the Raspberry Pi Model B+ https://www.raspberrypi-spy.co.uk/2018/03/introducing-raspberry-pi-3-b-plus-computer/Zorbas, D., Di Puglia Pugliese, L., Razafindralambo, T., & Guerriero, F. (2016). Optimal drone placement and cost-efficient target coverage. Journal of Network and Computer Applications, 75, 16-31. doi:10.1016/j.jnca.2016.08.009Parra, L., Rocher, J., García, L., Lloret, J., Tomás, J., Romero, O., … Roig, B. (2018). Design of a WSN for smart irrigation in citrus plots with fault-tolerance and energy-saving algorithms. Network Protocols and Algorithms, 10(2), 95. doi:10.5296/npa.v10i2.1320

Architecture and communication protocol to monitor and control water quality and irrigation in agricultural environments

[ES] La introducción de soluciones tecnológicas en la agricultura permite reducir el uso de recursos y aumentar la producción de los cultivos. Además, la calidad del agua de regadío se puede monitorizar para asegurar la seguridad de los productos para el consumo humano. Sin embargo, la localización remota de la mayoría de los campos presenta un problema para proveer de cobertura inalámbrica a los nodos sensores y actuadores desplegados en los campos y los canales de agua para regadío. El trabajo presentado en esta tesis aborda el problema de habilitar la comunicación inalámbrica entre los dispositivos electrónicos desplegados para la monitorización de la calidad del agua y el campo a través de un protocolo de comunicación y arquitectura heterogéneos. La primera parte de esta tesis introduce los sistemas de agricultura de precisión (PA) y la importancia de la monitorización de la calidad del agua y el campo. Asimismo, las tecnologías que permiten la comunicación inalámbrica en sistemas PA y el uso de soluciones alternativas como el internet de las cosas bajo tierra (IoUT) y los vehículos aéreos no tripulados (UAV) se introducen también. Después, se realiza un análisis en profundidad del estado del arte respecto a los sensores para la monitorización del agua, el campo y las condiciones meteorológicas, así como sobre las tecnologías inalámbricas más empleadas en PA. Además, las tendencias actuales y los desafíos de los sistemas de internet de las cosas (IoT) para regadío, incluyendo las soluciones alternativas introducidas anteriormente, han sido abordados en detalle. A continuación, se presenta la arquitectura propuesta para el sistema, la cual incluye las áreas de interés para las actividades monitorización que incluye las áreas de los canales y el campo. A su vez, la descripción y los algoritmos de operación de los nodos sensores contemplados para cada área son proporcionados. El siguiente capítulo detalla el protocolo de comunicación heterogéneo propuesto, incluyendo los mensajes y alertas del sistema. Adicionalmente, se presenta una nueva topología de árbol para redes híbridas LoRa/WiFi multisalto. Las funcionalidades específicas adicionales concebidas para la arquitectura propuesta están descritas en el siguiente capítulo. Éstas incluyen algoritmos de agregación de datos para la topología propuesta, un esquema de las amenazas de seguridad para los sistemas PA, algoritmos de ahorro de energía y tolerancia a fallos, comunicación bajo tierra para IoUT y el uso de drones para adquisición de datos. Después, los resultados de las simulaciones para las soluciones propuestas anteriormente son presentados. Finalmente, se tratan las pruebas realizadas en entornos reales para el protocolo heterogéneo presentado, las diferentes estrategias de despliegue de los nodos empleados, el consumo energético y la función de cuantificación de fruta. Estas pruebas demuestran la validez de la arquitectura y protocolo de comunicación heterogéneos que se han propuesto.[CA] La introducció de solucions tecnològiques en l'agricultura permet reduir l'ús de recursos i augmentar la producció dels cultius. A més, la qualitat de l'aigua de regadiu es pot monitoritzar per assegurar la qualitat dels productes per al consum humà. No obstant això, la localització remota de la majoria dels camps presenta un problema per a proveir de cobertura sense fils als nodes sensors i actuadors desplegats als camps i els canals d'aigua per a regadiu. El treball presentat en aquesta tesi tracta el problema d'habilitar la comunicació sense fils entre els dispositius electrònics desplegats per a la monitorització de la qualitat de l'aigua i el camp a través d'un protocol de comunicació i arquitectura heterogenis. La primera part d'aquesta tesi introdueix els sistemes d'agricultura de precisió (PA) i la importància de la monitorització de la qualitat de l'aigua i el camp. Així mateix, també s'introdueixen les tecnologies que permeten la comunicació sense fils en sistemes PA i l'ús de solucions alternatives com l'Internet de les coses sota terra (IoUT) i els vehicles aeris no tripulats (UAV). Després, es realitza una anàlisi en profunditat de l'estat de l'art respecte als sensors per a la monitorització de l'aigua, el camp i les condicions meteorològiques, així com sobre les tecnologies sense fils més emprades en PA. S'aborden les tendències actuals i els reptes dels sistemes d'internet de les coses (IoT) per a regadiu, incloent les solucions alternatives introduïdes anteriorment. A continuació, es presenta l'arquitectura proposada per al sistema, on s'inclouen les àrees d'interès per a les activitats monitorització en els canals i el camp. Finalment, es proporciona la descripció i els algoritmes d'operació dels nodes sensors contemplats per a cada àrea. El següent capítol detalla el protocol de comunicació heterogeni proposat, així como el disseny del missatges i alertes que el sistema proposa. A més, es presenta una nova topologia d'arbre per a xarxes híbrides Lora/WiFi multi-salt. Les funcionalitats específiques addicionals concebudes per l'arquitectura proposada estan descrites en el següent capítol. Aquestes inclouen algoritmes d'agregació de dades per a la topologia proposta, un esquema de les alertes de seguretat per als sistemes PA, algoritmes d'estalvi d'energia i tolerància a fallades, comunicació per a IoUT i l'ús de drons per a adquisició de dades. Després, es presenten els resultats de les simulacions per a les solucions proposades. Finalment, es duen a terme les proves en entorns reals per al protocol heterogeni dissenyat. A més s'expliquen les diferents estratègies de desplegament dels nodes empleats, el consum energètic, així com, la funció de quantificació de fruita. Els resultats d'aquetes proves demostren la validesa de l'arquitectura i protocol de comunicació heterogenis propost en aquesta tesi.[EN] The introduction of technological solutions in agriculture allows reducing the use of resources and increasing the production of the crops. Furthermore, the quality of the water for irrigation can be monitored to ensure the safety of the produce for human consumption. However, the remote location of most fields presents a problem for providing wireless coverage to the sensing nodes and actuators deployed on the fields and the irrigation water canals. The work presented in this thesis addresses the problem of enabling wireless communication among the electronic devices deployed for water quality and field monitoring through a heterogeneous communication protocol and architecture. The first part of the dissertation introduces Precision Agriculture (PA) systems and the importance of water quality and field monitoring. In addition, the technologies that enable wireless communication in PA systems and the use of alternative solutions such as Internet of Underground Things (IoUT) and Unmanned Aerial Vehicles (UAV) are introduced as well. Then, an in-depth analysis on the state of the art regarding the sensors for water, field and meteorology monitoring and the most utilized wireless technologies in PA is performed. Furthermore, the current trends and challenges for Internet of Things (IoT) irrigation systems, including the alternate solutions previously introduced, have been discussed in detail. Then, the architecture for the proposed system is presented, which includes the areas of interest for the monitoring activities comprised of the canal and field areas. Moreover, the description and operation algorithms of the sensor nodes contemplated for each area is provided. The next chapter details the proposed heterogeneous communication protocol including the messages and alerts of the system. Additionally, a new tree topology for hybrid LoRa/WiFi multi-hop networks is presented. The specific additional functionalities intended for the proposed architecture are described in the following chapter. It includes data aggregation algorithms for the proposed topology, an overview on the security threats of PA systems, energy-saving and fault-tolerance algorithms, underground communication for IoUT, and the use of drones for data acquisition. Then, the simulation results for the solutions previously proposed are presented. Finally, the tests performed in real environments for the presented heterogeneous protocol, the different deployment strategies for the utilized nodes, the energy consumption, and a functionality for fruit quantification are discussed. These tests demonstrate the validity of the proposed heterogeneous architecture and communication protocol.García García, L. (2021). Architecture and communication protocol to monitor and control water quality and irrigation in agricultural environments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17422

Sensors and Technologies in Spain: State-of-the-Art

The aim of this special issue was to provide a comprehensive view on the state-of-the-art sensor technology in Spain. Different problems cause the appearance and development of new sensor technologies and vice versa, the emergence of new sensors facilitates the solution of existing real problems. [...

Development of wireless network planning software for rural community use

Rural New Zealand has poor access to broadband Internet. The CRCnet project at the University of Waikato identified point-to-point wireless technology as an appropriate solution, and built networks for rural communities. The project identified viable solutions using low-cost wireless technologies and commodity hardware, allowing them to establish general construction guidelines for planning rural wireless networks. The CRCnet researchers speculated that these general construction guidelines had simplified the wireless network problem to a point at which it seemed feasible to embed the guidelines within a software tool. A significant observation by the CRCnet researchers was that community members are collectively aware of much of the local information that is required in the planning process. Bringing these two ideas together, this thesis hypothesises that a software tool could be designed to enable members of rural communities to plan their own wireless networks. To investigate this hypothesis, a wireless network planning system (WiPlan) was developed. WiPlan includes a tutorial that takes the unique approach of teaching the user process rather than the detail of network planning. WiPlan was evaluated using a novel evaluation technique structured as a roleplaying game. The study design provided participants with local knowledge appropriate for their planning roles. In two trials, WiPlan was found to support participants in successfully planning feasible networks, soliciting local knowledge as needed throughout the planning process. Participants in both trials were able to use the techniques introduced by the tutorial while planning their wireless network and successfully plan feasible wireless networks within budget in both study trials. This thesis explores the feasibility of designing a wireless networking planning tool, that can assist members of rural communities with no expertise in wireless network planning, to plan a feasible network and provides reasonable evidence to support the claim that such a planning tool is feasible

Routing, Localization And Positioning Protocols For Wireless Sensor And Actor Networks

Wireless sensor and actor networks (WSANs) are distributed systems of sensor nodes and actors that are interconnected over the wireless medium. Sensor nodes collect information about the physical world and transmit the data to actors by using one-hop or multi-hop communications. Actors collect information from the sensor nodes, process the information, take decisions and react to the events. This dissertation presents contributions to the methods of routing, localization and positioning in WSANs for practical applications. We first propose a routing protocol with service differentiation for WSANs with stationary nodes. In this setting, we also adapt a sports ranking algorithm to dynamically prioritize the events in the environment depending on the collected data. We extend this routing protocol for an application, in which sensor nodes float in a river to gather observations and actors are deployed at accessible points on the coastline. We develop a method with locally acting adaptive overlay network formation to organize the network with actor areas and to collect data by using locality-preserving communication. We also present a multi-hop localization approach for enriching the information collected from the river with the estimated locations of mobile sensor nodes without using positioning adapters. As an extension to this application, we model the movements of sensor nodes by a subsurface meandering current mobility model with random surface motion. Then we adapt the introduced routing and network organization methods to model a complete primate monitoring system. A novel spatial cut-off preferential attachment model and iii center of mass concept are developed according to the characteristics of the primate groups. We also present a role determination algorithm for primates, which uses the collection of spatial-temporal relationships. We apply a similar approach to human social networks to tackle the problem of automatic generation and organization of social networks by analyzing and assessing interaction data. The introduced routing and localization protocols in this dissertation are also extended with a novel three dimensional actor positioning strategy inspired by the molecular geometry. Extensive simulations are conducted in OPNET simulation tool for the performance evaluation of the proposed protocol