1,381 research outputs found

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

    Reading and storage of library resources using UHF RFID technology with IoT

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    Libraries supervisors have the administrative duty of control and keep safe their inventories, such as books, documents, manuals, and theses, facilitating access to their users to this information and helping them loan and return, internal or external, in case it’s permitted. We wanted to design and build a prototype for a device capable of complementing these tasks in a low cost. We go through the processes in the design of a prototype for a simultaneous Radio Frequency Identification Reader using Ultra High Frequencies with Internet of Things technologies for data storage and communication between multiple stations, to do so we use a decision matrix method to select hardware tools, and software programming languages and libraries, needed to build such device, comparing, and weighting the characteristics that fit our needs. The resulting hardware selection was the Raspberry Pi and the RedBoard with a 59,7% and 12,4% respectively, and NodeJS with WebSockets for the software selection with a 53,8%. Finally, we present the designed architecture and a working prototype of the device that was built. Obtained response times from the reader and the database storage were as low as 10 milliseconds and as high as 20 milliseconds

    Adapting omnichannel strategies to answer post-pandemic consumers' evolved in-store shopping expectations

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    Technology-infused omnichannel strategies have solidified their role in the turbulent environment of retailing. The advantages of such retailing approaches have been recognised during the interminable rise of e-commerce in the past decades, but the physical resurgence of consumers after the global pandemic evolved omnichannel expectations to new standards. Now, consumers desire a blend of online convenience in physical stores, driving retailers to adapt their technological capabilities to ensure seamless in-store shopping experiences. Because omnichanneling has become a necessity, retailers need to possess the understanding of providing valuable customer journeys. To offer insights and perspectives around the novel shift in physical retailing, this thesis was conducted as a two-case study, examining two retail giants that have emerged from opposite sides, the physical-first Target and online-dominant Amazon. To gain recent knowledge from the two companies, mainly qualitative secondary data was collected from diverse online sources, which were scrutinised employing content analysis and thematic synthesis. The longitudinal time horizon allowed for a progressive viewpoint to be constructed regarding the evolving dynamics between online and offline channels, and the role of technological implementations. The results of this thesis firstly sum up the expectations of consumers that have evolved pre- and post-pandemic, mainly the pursuit of convenience, continuity, and hedonistic aspects. Furthermore, this thesis explores various innovative technological features and how they can be integrated into physical stores to support seamless omnichannel expectations. In line with the results, the thesis suggests that most widely adapted technologies within case companies are scattered between the many phases of the shopping journey, either designed to complement the shopping experience by enhancing the favoured attributes, make the in-store interactions and steps more autonomous, or automate back-end operations. These technologies can be joined as a part of cohesive omnichannel experiences to contribute to borderless channel integration, all-inclusive offerings, and personalisation. The findings demonstrate that both case companies have explicit connections with theoretical frameworks. Along with the findings and synthesis, this thesis reinforces the discourse of post- pandemic omnichannel experiences and supplies real-life examples of diverse strategic uses of in-store technologies.Teknologiapohjaiset omnikanavastrategiat ovat vakiinnuttaneet asemansa vähittäiskaupan epävakaassa ympäristössä. Tällaisten vähittäismyyntitapojen edut ovat tiedostettu viime vuosikymmeninä verkkokaupankäynnin jatkuvan nousun aikana, mutta kuluttajien fyysinen palaaminen maailmanlaajuisen pandemian jälkeen nosti omnikanavaodotukset uusiin standardeihin. Nykyään kuluttajat mielivät yhdistelmiä verkkokaupan etuja fyysisissä myymälöissä, mikä ajaa vähittäismyyjiä mukauttamaan teknologisia valmiuksiaan varmistaakseen saumattoman ostoskokemuksen myymälässä. Koska omnikanavointi on muodostunut välttämättömyydeksi, vähittäismyyjien on ymmärrettävä, miten tarjota arvokkaita asiakasmatkoja. Tarjotakseen näkemyksiä ja perspektiivejä fyysisen vähittäiskaupan tuoreesta muutoksesta, tämä pro gradu -tutkielma toteutettiin tapaustutkimuksena tarkastellen kahta vastakkaiset lähtökohdat omaavaa vähittäiskaupan jättiläistä, kivijalkalähtöistä Targetia ja verkkovaltaista Amazonia. Molemmista yrityksistä hankittiin ajantasaista tietoa, pääasiassa laadullista sekundääridataa monipuolisista verkkolähteistä, jotka tarkasteltiin sisällönanalyysin ja teemasynteesin avulla. Pitkittäistutkimuksen aikajänne mahdollisti progressiivisen näkökulman muodostamisen verkkokanavien ja fyysisten kanavien välillä muuttuvista dynamiikoista ja toteutettujen teknologioiden roolista. Tämän tutkielman tulokset tiivistävät kuluttajien odotukset, jotka ovat kehittyneet ennen ja jälkeen pandemian, pääasiassa mukavuuden, jatkuvuuden ja hedonististen näkökohtien osalta. Lisäksi tutkielma tutustuu erilaisiin innovatiivisiin teknologiaominaisuuksiin ja siihen, miten niitä voidaan integroida fyysisiin myymälöihin edesauttamaan saumattomia omnikanavaodotuksia. Tulosten mukaisesti tutkielma ehdottaa, että tapaustutkimusyritysten laajimmin omaksutut teknologiat ovat hajallaan monissa ostosmatkan vaiheissa, joko suunniteltu täydentämään ostoskokemusta korostamalla haluttuja piirteitä, itsenäistämään myymälässä tapahtuvat vuorovaikutukset ja ostovaiheet tai automatisoimaan taustaprosesseja. Nämä teknologiat voidaan yhdistää osaksi yhtenäisiä omnikanavakokemuksia edistämään saumattomia kanavaintegraatioita, kaiken kattavaa tarjontaa ja personointia. Tutkimuksen löydökset osoittavat, että molemmilla tapaustutkimusyrityksillä on selviä yhteyksiä teoreettisiin viitekehyksiin. Löydösten ja synteesin ohella tämä tutkielma vahvistaa pandemian jälkeistä omnikanavakokemuksia koskevaa keskustelua ja tarjoaa todellisia esimerkkejä erilaisten myymäläteknologioiden strategisista käyttötavoista

    Improving approaches to material inventory management in construction industry in the UK

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    Materials used in construction constitute a major proportion of the total cost of construction projects. An important factor of great concern that adversely affects construction projects is the location and tracking of materials, which normally come in bulk with minimal identification. There is inadequate integration of modern wireless technologies (such as Radio Frequency Identification (RFID), Personal Digital Assistant (PDA) or Just-in-Time (JIT)) into project management systems for easier and faster materials management and tracking and to overcome human error. This research focuses on improving approaches to material inventory management in the UK construction industry through the formulation of RFID-based materials management tracking process system with projects. Existing literature review identified many challenges/problems in material inventory management on construction projects, such as supply delays, shortages, price fluctuations, wastage and damage, and insufficient storage space. Six construction projects were selected as exploratory case studies and cross-case analysis was used to investigate approaches to material inventory management practices: problems, implementation of ICT, and the potential for using emerging wireless technologies and systems (such as RFID and PDA) for materials tracking. Findings showed that there were similar problems of storage constraints and logistics with most of the construction projects. The synthesis of good practices required the implementation of RFID-facilitated construction management of materials tracking system to make material handling easier, quicker, more efficient and less paperwork. There was also a recommendation to implement Information and Communication Technology (ICT) tools to integrate plant, labour and materials into one system. The findings from the cases studies and the literature review were used to formulate a process for real-time material tracking using Radio Frequency Identification (RFID) that can improve material inventory management in the UK construction industry. Testing and validation undertaken assisted in formulating a process that can be useful, functional and acceptable for a possible process system’s development. Finally, research achievements/contributions to knowledge, and limitations were discussed and some suggestions for further research were outlined

    Cooperative Vehicle Perception and Localization Using Infrastructure-based Sensor Nodes

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    Reliable and accurate Perception and Localization (PL) are necessary for safe intelligent transportation systems. The current vehicle-based PL techniques in autonomous vehicles are vulnerable to occlusion and cluttering, especially in busy urban driving causing safety concerns. In order to avoid such safety issues, researchers study infrastructure-based PL techniques to augment vehicle sensory systems. Infrastructure-based PL methods rely on sensor nodes that each could include camera(s), Lidar(s), radar(s), and computation and communication units for processing and transmitting the data. Vehicle to Infrastructure (V2I) communication is used to access the sensor node processed data to be fused with the onboard sensor data. In infrastructure-based PL, signal-based techniques- in which sensors like Lidar are used- can provide accurate positioning information while vision-based techniques can be used for classification. Therefore, in order to take advantage of both approaches, cameras are cooperatively used with Lidar in the infrastructure sensor node (ISN) in this thesis. ISNs have a wider field of view (FOV) and are less likely to suffer from occlusion. Besides, they can provide more accurate measurements since they are fixed at a known location. As such, the fusion of both onboard and ISN data has the potential to improve the overall PL accuracy and reliability. This thesis presents a framework for cooperative PL in autonomous vehicles (AVs) by fusing ISN data with onboard sensor data. The ISN includes cameras and Lidar sensors, and the proposed camera Lidar fusion method combines the sensor node information with vehicle motion models and kinematic constraints to improve the performance of PL. One of the main goals of this thesis is to develop a wind induced motion compensation module to address the problem of time-varying extrinsic parameters of the ISNs. The proposed module compensates for the effect of the motion of ISN posts due to wind or other external disturbances. To address this issue, an unknown input observer is developed that uses the motion model of the light post as well as the sensor data. The outputs of the ISN, the positions of all objects in the FOV, are then broadcast so that autonomous vehicles can access the information via V2I connectivity to fuse with their onboard sensory data through the proposed cooperative PL framework. In the developed framework, a KCF is implemented as a distributed fusion method to fuse ISN data with onboard data. The introduced cooperative PL incorporates the range-dependent accuracy of the ISN measurements into fusion to improve the overall PL accuracy and reliability in different scenarios. The results show that using ISN data in addition to onboard sensor data improves the performance and reliability of PL in different scenarios, specifically in occlusion cases

    Role of RFID Technology in Engineering Applications

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    This paper provides an extensive overview of Radio Frequency Identification technology (RFID) and its applications across different industries, rather than focusing on recent developments alone. Due to the multidisciplinary nature of RFID, proficiency in various engineering fields is necessary to fully comprehend this technology. As the use of RFID continues to expand in various industries, it is imperative to educate engineers and professionals to better understand this technology. An RFID system typically consists of tags, readers, antennae, and software, and various factors such as reading range, frequency range, and environmental considerations must be taken into account when designing such a system. Security must also be a key consideration in the development of an RFID system. To incorporate RFID technology into traditional engineering curricula, this study proposes emphasizing its connection to traditional fields such as electrical, computer, and artificial engineering

    An Efficient Intelligent Semi-Automated Warehouse Inventory Stocktaking System

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    In the context of evolving supply chain management, the significance of efficient inventory management has grown substantially for businesses. However, conventional manual and experience-based approaches often struggle to meet the complexities of modern market demands. This research introduces an intelligent inventory management system to address challenges related to inaccurate data, delayed monitoring, and overreliance on subjective experience in forecasting. The proposed system integrates bar code and distributed flutter application technologies for intelligent perception, alongside comprehensive big data analytics to enable data-driven decision-making. Through meticulous analysis, system design, critical technology exploration, and simulation validation, the effectiveness of the proposed system is successfully demonstrated. The intelligent system facilitates second-level monitoring, high-frequency checks, and artificial intelligence-driven forecasting, consequently enhancing the automation, precision, and intelligence of inventory management. This system contributes to cost reduction and optimized inventory sizes through accurate predictions and informed decisions, ultimately achieving a mutually beneficial scenario. The outcomes of this research offe

    Autonomous Sensing Nodes for IoT Applications

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    The present doctoral thesis fits into the energy harvesting framework, presenting the development of low-power nodes compliant with the energy autonomy requirement, and sharing common technologies and architectures, but based on different energy sources and sensing mechanisms. The adopted approach is aimed at evaluating multiple aspects of the system in its entirety (i.e., the energy harvesting mechanism, the choice of the harvester, the study of the sensing process, the selection of the electronic devices for processing, acquisition and measurement, the electronic design, the microcontroller unit (MCU) programming techniques), accounting for very challenging constraints as the low amounts of harvested power (i.e., [μW, mW] range), the careful management of the available energy, the coexistence of sensing and radio transmitting features with ultra-low power requirements. Commercial sensors are mainly used to meet the cost-effectiveness and the large-scale reproducibility requirements, however also customized sensors for a specific application (soil moisture measurement), together with appropriate characterization and reading circuits, are also presented. Two different strategies have been pursued which led to the development of two types of sensor nodes, which are referred to as 'sensor tags' and 'self-sufficient sensor nodes'. The first term refers to completely passive sensor nodes without an on-board battery as storage element and which operate only in the presence of the energy source, provisioning energy from it. In this thesis, an RFID (Radio Frequency Identification) sensor tag for soil moisture monitoring powered by the impinging electromagnetic field is presented. The second term identifies sensor nodes equipped with a battery rechargeable through energy scavenging and working as a secondary reserve in case of absence of the primary energy source. In this thesis, quasi-real-time multi-purpose monitoring LoRaWAN nodes harvesting energy from thermoelectricity, diffused solar light, indoor white light, and artificial colored light are presented

    Exploring Cloud Adoption Possibilities for the Manufacturing Sector: A Role of Third-Party Service Providers

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    As the manufacturing sector strides towards digitalization under the influence of Industry 4.0, cloud services have emerged as the new norm, driving change and innovation in this rapidly transforming landscape. This study investigates the possibilities of cloud adoption in the manufacturing sector by developing a conceptual model to identify suitable cloud-based solutions and explores the role of third-party service providers in aiding manufacturers throughout their cloud adoption journey. The research methods consist of a comprehensive literature review of the manufacturing industry, digital transformation, cloud computing, etc., followed by qualitative analyses of industrial benchmarks case studies and an investigation into an application of the developed model to a hypothetical food manufacturing company as an example. This study indicates that cloud adoption can yield substantial benefits in the manufacturing sector, including operational efficiency, cost reduction, and innovation, etc. The study concludes that the developed conceptual model provides a practical framework to identify the most suitable cloud-based solutions during the cloud adoption process in the manufacturing context. In addition, third-party service providers like Capgemini are capable of not only filling the technical gaps but also consulting strategic directions and innovations for their client organizations, hence playing a vital role in driving the industrial digital transformation process. With an extensive mapping of their capabilities, a set of recommendations intended to assist Capgemini in enhancing capabilities and improving competitive performance in the market has been offered

    A Handheld Fine-Grained RFID Localization System with Complex-Controlled Polarization

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    There is much interest in fine-grained RFID localization systems. Existing systems for accurate localization typically require infrastructure, either in the form of extensive reference tags or many antennas (e.g., antenna arrays) to localize RFID tags within their radio range. Yet, there remains a need for fine-grained RFID localization solutions that are in a compact, portable, mobile form, that can be held by users as they walk around areas to map them, such as in retail stores, warehouses, or manufacturing plants. We present the design, implementation, and evaluation of POLAR, a portable handheld system for fine-grained RFID localization. Our design introduces two key innovations that enable robust, accurate, and real-time localization of RFID tags. The first is complex-controlled polarization (CCP), a mechanism for localizing RFIDs at all orientations through software-controlled polarization of two linearly polarized antennas. The second is joint tag discovery and localization (JTDL), a method for simultaneously localizing and reading tags with zero-overhead regardless of tag orientation. Building on these two techniques, we develop an end-to-end handheld system that addresses a number of practical challenges in self-interference, efficient inventorying, and self-localization. Our evaluation demonstrates that POLAR achieves a median accuracy of a few centimeters in each of the x/y/z dimensions in practical indoor environments
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