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Four trials across Ontario were sampled to evaluate the effects of best management practices (BMP) on six soil health indicators (SHI). As well, the use of near infrared (NIR) and mid infrared (MIR) spectroscopy to predict SHI was explored at site and regional levels. Lastly, MIR spectroscopy was utilized to identify differences in soils under differing BMPs. The study found no-tillage (NT) improved SHI values at two of three sites. Inclusion of cover crops and small grains in rotation improved SHI values at one site, while no significant differences were found at two sites. The study found that MIR models predicted SHI better than NIR models. As well, the use of competitive adaptive reweighted sampling (CARS) feature selection improved model performance compared to full spectra models. Lastly, differences were found between MIR spectra from soils under NT and moldboard plow treatments and between annual versus perennial crop rotations. Ontario Agri-Food Innovation Alliance

[ES] El Internet de las Cosas (IoT) ha experimentado un gran crecimiento en los últimos años. El incremento en el número de dispositivos, una mayor miniaturización de la capacidad de computación y las técnicas de virtualización, han favorecido su adopción en la industria y en otros sectores. Asimismo, la introducción de nuevas tecnologías (como la Inteligencia Artificial, el 5G, el Tactile Internet o la Realidad Aumentada) y el auge del edge computing preparan el terreno, y formulan los requisitos, para lo que se conoce como Internet de las Cosas de Nueva Generación (NGIoT). Estos avances plantean nuevos desafíos tales como el establecimiento de arquitecturas que cubran dichas necesidades y a la vez resulten flexibles, escalables y prácticas para implementar servicios que aporten valor a la sociedad. En este sentido, el IoT puede resultar un elemento clave para el establecimiento de políticas y la toma de decisiones. Una herramienta muy útil para ello es la definición y cálculo de indicadores compuestos, que representan un impacto en un fenómeno real a través de un único valor. La generación de estos indicadores es un aspecto promovido por entidades oficiales como la Unión Europea, aunque su automatización y uso en entornos de tiempo real es un campo poco explorado. Este tipo de índices deben seguir una serie de operaciones matemáticas y formalidades (normalización, ponderación, agregación¿) para ser considerados válidos. Esta tesis doctoral plantea la unión de ambos campos en alza, proponiendo una arquitectura de Internet de las Cosas de nueva generación orientada al servicio de cálculo y predicción de indicadores compuestos. Partiendo de la experiencia del candidato en proyectos de investigación europeos y regionales, y construyendo sobre tecnologías open source, se ha incluido el diseño, desarrollo e integración de los módulos de dicha arquitectura (adquisición de datos, procesamiento, visualización y seguridad) como parte de la tesis. Dichos planteamientos e implementaciones se han validado en cinco escenarios diferentes, cubriendo cinco índices compuestos en entornos con requisitos dispares siguiendo una metodología diseñada durante este trabajo. Los casos de uso están centrados en aspectos de sostenibilidad en entornos urbano y marítimo-portuario, pero se ha destacado que la solución puede ser extrapolada a otros sectores ya que ha sido diseñada de una manera agnóstica. El resultado de la tesis ha sido, además, analizado desde el punto de vista de transferencia tecnológica. Se ha propuesto la formulación de un producto, así como una posible financiación en fases de madurez más avanzadas y su potencial explotación como elemento comercializable [CA] La Internet de les Coses (IoT) ha experimentat un gran creixement en els últims anys. L'increment en el nombre de dispositius, una major miniaturització de la capacitat de computació i les tècniques de virtualització, han afavorit la seua adopció en la indústria i en altres sectors. Així mateix, la introducció de noves tecnologies (com la Intel·ligència Artificial, el 5G, la Internet Tàctil o la Realitat Augmentada) i l'auge del edge computing preparen el terreny, i formulen els requisits, per al que es coneix com a Internet de les Coses de Nova Generació (NGIoT). Aquests avanços plantegen nous desafiaments com ara l'establiment d'arquitectures que cobrisquen aquestes necessitats i resulten, alhora, flexibles, escalables i pràctiques per a implementar serveis que aporten valor a la societat. Ací, el IoT pot resultar un element clau per a l'establiment de polítiques i la presa de decisions. Una eina molt útil en aquest sentit és la definició i càlcul d'indicadors compostos, que representen un impacte en un fenomen real a través d'un únic valor. La generació d'aquests indicadors és un aspecte promogut per entitats oficials com la Unió Europea, encara que la seua automatització i ús en entorns de temps real és un camp poc explorat. Aquest tipus d'índexs han de seguir una sèrie d'operacions matemàtiques i formalitats (normalització, ponderació, agregació¿) per a ser considerats vàlids. Aquesta tesi doctoral planteja la unió de tots dos camps en alça, proposant una arquitectura d'Internet de les Coses de nova generació orientada al servei de càlcul i predicció d'indicadors compostos. Partint de l'experiència del candidat en projectes d'investigació europeus i regionals, i construint sobre tecnologies open source, s'ha inclòs el disseny, desenvolupament i integració dels mòduls d'aquesta arquitectura (adquisició de dades, processament, visualització i seguretat) com a part de la tesi. Aquests plantejaments i implementacions s'han validat en cinc escenaris diferents, cobrint cinc índexs compostos en entorns amb requisits dispars seguint una metodologia dissenyada durant aquest treball. Els casos d'ús estan centrats en aspectes de sostenibilitat en entorns urbà i marítim-portuari, però s'ha destacat que la solució pot ser extrapolada a altres sectors ja que ha sigut dissenyada d'una manera agnòstica. El resultat de la tesi ha sigut, a més, analitzat des del punt de vista de transferència tecnològica. S'ha proposat la formulació d'un producte, així com un possible finançament en fases de maduresa més avançades i la seua potencial explotació com a element comercialitzable [EN] The Internet of Things (IoT) has experienced tremendous growth in recent years. The increase in the number of devices, greater miniaturization of computing capacity and virtualization techniques have favored its adoption in industry and other sectors. Likewise, the introduction of new technologies (such as Artificial Intelligence, 5G, Tactile Internet or Augmented Reality), together with the rise of edge computing, are paving the way, and formulating the requirements, for what is known as the Next Generation Internet of Things (NGIoT). These advances pose new challenges such as the establishment of proper architectures that meet those needs and, at the same time, are flexible, scalable, and practical for implementing services that bring value to society. In this sense, IoT could be a key element for policy and decision making. A very useful tool for this is the definition and calculation of composite indicators, which represent an impact on a real phenomenon through a single value. The generation of these indicators is an aspect promoted by official entities such as the European Union, although their automation and use in real-time environments is a rather uncharted research field. This type of indexes must follow a series of mathematical operations and formalities (normalization, weighting, aggregation...) to be considered valid. This doctoral thesis proposes the union of both fields, proposing a new generation Internet of Things architecture oriented to the calculation and prediction of composite indicators. Based on the candidate's experience in European and regional research projects, and building on open source technologies, the design, development and integration of the modules of such architecture (data acquisition, processing, visualization and security) has been included as part of the thesis. These approaches and implementations have been validated in five different scenarios, covering five composite indexes in environments with disparate requirements following a methodology designed during this work. The use cases are focused on sustainability aspects in urban and maritime-port environments, but it has been highlighted that the solution can be extrapolated to other sectors as it has been designed in an agnostic way. The result of the thesis has also been analyzed from the point of view of technology transfer. A tentative product definition has been formulated, as well as a possible financing in more advanced stages of maturity and its potential exploitation as a marketable element

The mobilization of scientific knowledge for agricultural application has long been supported by Radio broadcast in Africa. Digital radio and mobile phone integration are becoming linked with radio and physical extension services, known as Radio+. Farm Radio International provides radio extension services in Ghana and participated in a research attachment for this study. There is a need to improve the content and delivery of agricultural extension services. The study utilized Collaborative Inquiry interviews, a process involving semi-structured, in-depth and interactive discussions. Farm Radio International employees were the interview demographic. The interview data was analyzed using a deductive thematic coding process using NVivo. Issues with funding and capacity, participatory processes, and digital development consistently effect all sectors of agricultural extension in Ghana. Based on these results, the recommendation provided is the development of a digital extension application to serve as a mobile communications and information hub to farmers in rural Ghana.

Globally, species are experiencing geographical range shifts as a result of increased frequency and severity of extreme weather events exceeding their realized thermal niche boundaries. Using thermal limit approximations, relative heat indices can predict species extinction-colonization patterns over broad spatial scales. Locally, microclimate refugia can act as buffers against short term thermal extremes and improve species persistence probabilities. Opportunities to explore the role of microclimates in local species extinctions have recently emerged with advances in unmanned aerial vehicle (UAV) and thermal imaging technologies. My first chapter proposed a UAV-based methodology facilitating direct and accurate air temperature measurements at biologically relevant scales for butterfly species. These high-resolution microclimate measurements enabled broad-scale thermal limit approximation model applications to patch-level measurements using a verified thermal positioning index. In my second chapter, I evaluated the applicability of broad-scale models for predictions of local species distributions and abundances. The methodology proposed in Chapter 1 was used to generate patch-specific thermal position indices for butterfly species observed and surveyed in our study patches. Patch-level measurements of thermally tolerable area (overheating index) helped predict aspects of butterfly abundance, presence, and overall species richness, along with other environmental metrics that are relevant for butterfly biology. This thesis explores a frontier of direct UAV-based microclimate measurements and underscores the importance of considering thermal extremes to understand butterfly distribution and abundance, even in protected habitats.

Maize black layer (BL) is the developmental stage where plants reach physiological maturity, which is a desirable trait, but phenotyping this trait is time consuming and costly. Any tool enabling high-throughput phenotyping of BL would be an invaluable asset for developing or maintaining short-season maize hybrids. This thesis investigated the potential of using remote sensing (RS) technologies to detect BL. The spectral signatures of 16 short-season maize hybrids were captured using a ground-based hyperspectral sensor through the late grain filling period (GFP) which were then used to develop and test vegetation indices (VIs) that correlated with BL formation. Two of these VIs, the normalized green red difference index (NGRDI) and the novel VI.5 were highly accurate, specific, and had spectral curves that match the physiology of maize in the late GFP. These findings suggest that high-throughput phenotyping of maize BL is possible using RS technologies. Natural Sciences and Engineering Research Council (NSERC) Discovery Grant, Natural Sciences and Engineering Research Council (NSERC) Collaborative Research and Development (CRD) grant with the support of Maizex Seeds Inc.

Kebutuhan air pada tanaman merupakan hal yang penting bagi kondisi tanaman. Tanaman akan tumbuh dengan baik bila diberi perawatan yang benar, yaitu dengan cara menyiram dengan air yang cukup ketika tanah kering secara teratur serta menjaga kelembapan tanahnya, dan bila tanaman kekurangan atau kelebihan air dapat menyebabkan tanaman tidak tumbuh dengan baik dan bisa saja tanaman akan mati, dari permasalahan tersebut dibangun sebuah alat yang dapat memonitoring kelembapan tanah serta mengontrol penyiraman secara otomatis maupun manual, dengan memanfaatkan teknologi Internet of Things dan aplikasi telegram agar dapat memantau dan mengontrol melalui handphone. Alat ini menggunakan mikrokontroler ESP32 sebagai kontrol utama, yang terhubung dengan telegram. Pemantauan kelembaban tanah dilakukan menggunakan sensor YL-69, nantinya hasil pembacaan akan ditampilkan ke aplikasi telegram dan LCD, untuk penyiraman dapat dilakukan menggunakan aplikasi telegram atau ketika nilai kelembapan tanah kurang dari batas yang ditentukan, maka relay akan aktif untuk menyalakan pompa, untuk buka tutup kanopi, dapat dilakukan menggunakan aplikasi telegram atau melalui pembacaan sensor YL-83 jika terbaca kurang dari 2800, untuk mengecek kapasitas bak air menggunakan sensor ultrasonik HC-SR04. Waktu Respons pengontrolan sistem melalui telegram dipengaruhi oleh koneksi internet. The water requirement is vital for the condition of the plant, by giving the right care makes plants will grow well, regularly watering when the soil is dry and keeping the soil moist, and if the plant lacks or has excess water it causes the plant not to grow properly and the plant may die, from these problems, a tool was built that can monitor soil moisture and control watering automatically or manually, by utilizing Internet of Things technology and the telegram application so that it can monitor and control via mobile phones. This tool uses an ESP32 microcontroller as the main control, which is connected to a telegram, to monitor the soil moisture using the YL-69 sensor, then the reading results will be displayed on the telegram application and LCD, watering can be done using the telegram application or else when the soil moisture value is less than the specified limit, the relay will activate to turn on the pump, to opening and closing the canopy can be done using the telegram application or the YL-83 sensor reading if it reads less than 2800, to check the capacity of the water tank using the ultrasonic sensor HC-SR04. The response time of controlling the system via telegram is affected by the internet connection.

Sri Lankans use Facebook (Fb) to communicate and share information. The virtual communities of practices (VCoPs) share knowledge and build relationships while encouraging learning and providing opportunities for doing business. Yet, online misinformation circulation threatens the information-sharing and learning process within VCoPs. Therefore, members of Fb communities could be easy targets of misinformation. This study explores how knowledge sharing and learning occur within Fb Virtual Communities in Sri Lanka with the threat of disseminating misinformation. The research findings revealed that while Fb VCoPs share knowledge related to diverse agricultural topics via different mediums to provide solutions to overcome the prevailing challenges in Sri Lankan agriculture, online misinformation threatens the sustainability of VCoPs. State interference, members’ violent behaviour, and lack of diverse content decrease members’ engagement. Research results highlight the importance of tackling the misinformation threat and the necessity of government support in developing the capacities of these VCoPs. 2023-12-31

Värkvõrk, ehk Asjade Internet (Internet of Things, lüh IoT) edendab lahendusi nagu nn tark linn, kus meid igapäevaselt ümbritsevad objektid on ühendatud infosüsteemidega ja ka üksteisega. Selliseks näiteks võib olla teekatete seisukorra monitoorimissüsteem. Võrku ühendatud sõidukitelt (nt bussidelt) kogutakse videomaterjali, mida seejärel töödeldakse, et tuvastada löökauke või lume kogunemist. Tavaliselt hõlmab selline lahendus keeruka tsentraalse süsteemi ehitamist. Otsuste langetamiseks (nt milliseid sõidukeid parasjagu protsessi kaasata) vajab keskne süsteem pidevat ühendust kõigi IoT seadmetega. Seadmete hulga kasvades võib keskne lahendus aga muutuda pudelikaelaks. Selliste protsesside disaini, haldust, automatiseerimist ja seiret hõlbustavad märkimisväärselt äriprotsesside halduse (Business Process Management, lüh BPM) valdkonna standardid ja tööriistad. Paraku ei ole BPM tehnoloogiad koheselt kasutatavad uute paradigmadega nagu Udu- ja Servaarvutus, mis tuleviku värkvõrgu jaoks vajalikud on. Nende puhul liigub suur osa otsustustest ja arvutustest üksikutest andmekeskustest servavõrgu seadmetele, mis asuvad lõppkasutajatele ja IoT seadmetele lähemal. Videotöötlust võiks teostada mini-andmekeskustes, mis on paigaldatud üle linna, näiteks bussipeatustesse. Arvestades IoT seadmete üha suurenevat hulka, vähendab selline koormuse jaotamine vähendab riski, et tsentraalne andmekeskust ülekoormamist. Doktoritöö uurib, kuidas mobiilsusega seonduvaid IoT protsesse taoliselt ümber korraldada, kohanedes pidevalt muutlikule, liikuvate seadmetega täidetud servavõrgule. Nimelt on ühendused katkendlikud, mistõttu otsuste langetus ja planeerimine peavad arvestama muuhulgas mobiilseadmete liikumistrajektoore. Töö raames valminud prototüüpe testiti Android seadmetel ja simulatsioonides. Lisaks valmis tööriistakomplekt STEP-ONE, mis võimaldab teadlastel hõlpsalt simuleerida ja analüüsida taolisi probleeme erinevais realistlikes stsenaariumites nagu seda on tark linn. The Internet of Things (IoT) promotes solutions such as a smart city, where everyday objects connect with info systems and each other. One example is a road condition monitoring system, where connected vehicles, such as buses, capture video, which is then processed to detect potholes and snow build-up. Building such a solution typically involves establishing a complex centralised system. The centralised approach may become a bottleneck as the number of IoT devices keeps growing. It relies on constant connectivity to all involved devices to make decisions, such as which vehicles to involve in the process. Designing, automating, managing, and monitoring such processes can greatly be supported using the standards and software systems provided by the field of Business Process Management (BPM). However, BPM techniques are not directly applicable to new computing paradigms, such as Fog Computing and Edge Computing, on which the future of IoT relies. Here, a lot of decision-making and processing is moved from central data-centers to devices in the network edge, near the end-users and IoT sensors. For example, video could be processed in mini-datacenters deployed throughout the city, e.g., at bus stops. This load distribution reduces the risk of the ever-growing number of IoT devices overloading the data center. This thesis studies how to reorganise the process execution in this decentralised fashion, where processes must dynamically adapt to the volatile edge environment filled with moving devices. Namely, connectivity is intermittent, so decision-making and planning need to involve factors such as the movement trajectories of mobile devices. We examined this issue in simulations and with a prototype for Android smartphones. We also showcase the STEP-ONE toolset, allowing researchers to conveniently simulate and analyse these issues in different realistic scenarios, such as those in a smart city. https://www.ester.ee/record=b5525514

When disaster strikes in urban areas, the devastating results are collapsed structures that may contain voids, and trapped people within. To a large extent, the speed with which these victims can be found and extricated determines the likelihood of their survival. Specially trained and equipped emergency first responders are tasked with trying to save their lives by locating and extricating trapped victims from these dangerous environments. Telepresence systems can help first responders search for casualties from a safe location. Most automated search systems intended for use in urban disasters, come in the form of remotely operated robots. This work takes a different approach to telepresence and robotics. This work is an extension of previous work that exploits the intelligence and characteristics of trained search dogs combined with compatible technology and used as components in new kinds of telepresence systems for urban search and rescue (USAR) operations. The Canine Remote Deployment System (CRDS) is a tool that emergency responders can use to deliver critical supplies to trapped victims in rubble using dogs. The first contribution of this work is the development of the bark detection system for automatically triggering deployment of packages near trapped victims from the CRDS-guaranteeing accurate package deployment even when remote communication with the dog is impossible. A well-known ground robot problem is the difficulty in designing a mobility mechanism to traverse rubble. Another contribution of this thesis is the Canine Assisted Robot Deployment (CARD) framework and the design of a robot capable of being carried by a search dog. This work extends the responder’s telepresence in rescue operations by bringing robots much deeper into the disaster site than current methods. Visual odometry is used in location tracking in GPS-denied environments and can be used in rescue operations. This research explores the limitation of RGB-D cameras for visual odometry for this application. An algorithm called pseudo-Random Interest Points Extractor was developed iv to track images over visually feature-sparse areas with the potential use of visually reconstructing canine search paths to victims. This work concentrates on using visual odometry from data collected from a search dog-mounted RGB-D camera. The task of model stabilization is difficult due to the nature of dog’s constant and unpredictable movements, asthe data contains many motion blurred images. The development of an algorithm called Intelligent Frame Selector is shown to improve visual odometry for systems carried by search dogs by intelligently filtering data and selecting only usable frames. The algorithm can be applied to any general visual odometry pipeline beneficially as the technique reduces cumulative error problems by using less data.

Jantung merupakan organ penting dalam tubuh manusia yang difungsikan untuk memompa darah ke seluruh tubuh. Untuk membantu memudahkan manusia dalam melakukan pemeriksaan detak jantung maka dalam penelitian ini menyajikan sebuah alat monitoring detak jantung dan suhu tubuh menggunakan Internet of Things. Internet of Things (IoT) adalah konsep dimana berbagai perangkat bersensor saling terhubung melalui internet untuk mengumpulkan dan mentransfer data. Dalam metode pengujian ini melibatkan 10 orang manahiswa, 1 orang anak-anak, 1 orang remaja, 1 orang dewasa, 1 orang lanjut usia, 1 orang dengan perokok aktif, 1 orang atlet dan 1 orang dengan berat badan berlebih (obesitas). Dalam pengujian ini menggunakan 2 buah sensor yaitu sensor MAX30105 sebagai sensor pengukuran detak jantung dan GY-906 sebagai sensor pengukur suhu tubuh. Dari hasil pengujian menggunakan alat pembanding error yang didapatkan rata-rata 0,06% untuk detak jantung dan 0,01 % untu suhu tubuh. Dalam pengujian sensor MAX30105 terdapat juga kadar oksigen dalam darah yang terdeteksi The heart is an important organ in the human body that functions to pump blood throughout the body. To help make it easier for humans to check their heart rate, this study presents a heart rate and body temperature monitoring tool using the Internet of Things. Internet of Things (IoT) is a concept where various sensor devices are interconnected via the internet to collect and transfer data. In this test method involved 10 students, 1 child, 1 teenager, 1 adult, 1 elderly person, 1 person with an active smoker, 1 athlete and 1 person with excess weight (obesity). In this test, 2 sensors are used, namely the MAX30105 sensor as a heart rate measurement sensor and the GY-906 as a body temperature sensor. From the test results using a comparison tool, the error obtained an average of 0.06% for heart rate and 0.01% for body temperature. In testing the MAX30105 sensor there is also a detectable level of oxygen in the blood.