Academic literature on the topic 'Cloud robotics drone'
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Journal articles on the topic "Cloud robotics drone"
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Roy, Swarnabha, Tony Vo, Steven Hernandez, Austin Lehrmann, Asad Ali, and Stavros Kalafatis. "IoT Security and Computation Management on a Multi-Robot System for Rescue Operations Based on a Cloud Framework." Sensors 22, no. 15 (July 26, 2022): 5569. http://dx.doi.org/10.3390/s22155569.
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There is a growing body of literature that recognizes the importance of Multi-Robot coordination and Modular Robotics. This work evaluates the secure coordination of an Unmanned Aerial Vehicle (UAV) via a drone simulation in Unity and an Unmanned Ground Vehicle (UGV) as a rover. Each robot is equipped with sensors to gather information to send to a cloud server where all computations are performed. Each vehicle is registered by blockchain ledger-based network security. In addition to these, relevant information and alerts are displayed on a website for the users. The usage of UAV–UGV cooperation allows for autonomous surveillance due to the high vantage field of view. Furthermore, the usage of cloud computation lowers the cost of microcontrollers by reducing their complexity. Lastly, blockchain technology mitigates the security issues related to adversarial or malicious robotic nodes connecting to the cluster and not agreeing to privacy rules and norms.
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Paul, P. K., R. R. Sinha, P. S. Aithal, Ricardo Saavedra, Bashiru Aremu, and S. Mewada. "Agricultural Robots: The Applications of Robotics in Smart Agriculture: towards More Advanced Agro Informatics Practice." Asian Review of Mechanical Engineering 9, no. 1 (May 5, 2020): 38–44. http://dx.doi.org/10.51983/arme-2020.9.1.2472.
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Robotics is a machine which is supported by the Artificial Intelligence and Expert Systems. This is basically run with the programmable computer which is run and does the performance and activities automatically. The robotics systems can be done with the integrated systems built inside or it may be done by the external controlling mechanism. It is not mandatory that a robot always looks like a human being. It could be of any form and designing or shape, however, the things in robotics is that it is operated automatically. Robots are applicable in diverse areas and sectors and among these important are include healthcare, business, agriculture, transportation, manufacturing etc. As far as agriculture is concerned, Robotics is very much associated with the various pre and postproduction of agriculture and similar sectors. Initially in harvesting only the robotics were used but currently, there are more concerns where robotics can be applicable viz. drone for the weed controlling, plant seeding, environmental assessing and monitoring, soil mapping and analysis, etc. Initially, only basic Information Technology tools were common in agricultural practices but in recent past, many technologies are using in agriculture and among these important are Cloud Computing, Big Data, HCI, Usability Engineering, Robotics and AI, etc. According to the market analysis companies the growth of the robotics is very increasing and will touch the high very soon. This paper talks about the basics of robotics including a special focus on agriculture. Paper also highlighted the areas of applications with the concern of issues and challenges in brief.
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Rodenberg, O. B. P. M., E. Verbree, and S. Zlatanova. "INDOOR A* PATHFINDING THROUGH AN OCTREE REPRESENTATION OF A POINT CLOUD." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W1 (October 5, 2016): 249–55. http://dx.doi.org/10.5194/isprs-annals-iv-2-w1-249-2016.
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There is a growing demand of 3D indoor pathfinding applications. Researched in the field of robotics during the last decades of the 20th century, these methods focussed on 2D navigation. Nowadays we would like to have the ability to help people navigate inside buildings or send a drone inside a building when this is too dangerous for people. What these examples have in common is that an object with a certain geometry needs to find an optimal collision free path between a start and goal point. <br><br> This paper presents a new workflow for pathfinding through an octree representation of a point cloud. We applied the following steps: 1) the point cloud is processed so it fits best in an octree; 2) during the octree generation the interior empty nodes are filtered and further processed; 3) for each interior empty node the distance to the closest occupied node directly under it is computed; 4) a network graph is computed for all empty nodes; 5) the A* pathfinding algorithm is conducted. <br><br> This workflow takes into account the connectivity for each node to all possible neighbours (face, edge and vertex and all sizes). Besides, a collision avoidance system is pre-processed in two steps: first, the clearance of each empty node is computed, and then the maximal crossing value between two empty neighbouring nodes is computed. The clearance is used to select interior empty nodes of appropriate size and the maximal crossing value is used to filter the network graph. Finally, both these datasets are used in A* pathfinding.
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Rafique, Adnan Ahmed, Ahmad Jalal, and Kibum Kim. "Automated Sustainable Multi-Object Segmentation and Recognition via Modified Sampling Consensus and Kernel Sliding Perceptron." Symmetry 12, no. 11 (November 23, 2020): 1928. http://dx.doi.org/10.3390/sym12111928.
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Object recognition in depth images is challenging and persistent task in machine vision, robotics, and automation of sustainability. Object recognition tasks are a challenging part of various multimedia technologies for video surveillance, human–computer interaction, robotic navigation, drone targeting, tourist guidance, and medical diagnostics. However, the symmetry that exists in real-world objects plays a significant role in perception and recognition of objects in both humans and machines. With advances in depth sensor technology, numerous researchers have recently proposed RGB-D object recognition techniques. In this paper, we introduce a sustainable object recognition framework that is consistent despite any change in the environment, and can recognize and analyze RGB-D objects in complex indoor scenarios. Firstly, after acquiring a depth image, the point cloud and the depth maps are extracted to obtain the planes. Then, the plane fitting model and the proposed modified maximum likelihood estimation sampling consensus (MMLESAC) are applied as a segmentation process. Then, depth kernel descriptors (DKDES) over segmented objects are computed for single and multiple object scenarios separately. These DKDES are subsequently carried forward to isometric mapping (IsoMap) for feature space reduction. Finally, the reduced feature vector is forwarded to a kernel sliding perceptron (KSP) for the recognition of objects. Three datasets are used to evaluate four different experiments by employing a cross-validation scheme to validate the proposed model. The experimental results over RGB-D object, RGB-D scene, and NYUDv1 datasets demonstrate overall accuracies of 92.2%, 88.5%, and 90.5% respectively. These results outperform existing state-of-the-art methods and verify the suitability of the method.
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Gambo, Nuru, and Innocent Musonda. "Effect of the Fourth Industrial Revolution on Road Transport Asset Management Practice in Nigeria." Journal of Construction in Developing Countries 26, no. 1 (July 30, 2021): 19–43. http://dx.doi.org/10.21315/jcdc2021.26.1.2.
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Poor management practices of road transport assets posed a challenge to the sustainable development of the transport system in developing countries like Nigeria. Studies in the past focused mainly on the performance of road construction process. However, few studies have evaluated the effect of the fourth Industrial Revolution (4.0IR) on the road transport assets in developing countries such as Nigeria. The current study aimed at assessing the effect of the 4.0IR towards improving the management practice of road transport assets. Survey instruments were administered to project and facility managers in the Nigerian road construction sector of the economy using a proportionate random sampling technique. Partial least square structural equation modelling was used for data analysis utilising the Warp 7.0 partial least squares-structural equation modelling (PLS-SEM) software algorithm. The software calculates p-values with WarpPLS based on non-parametric algorithms, resampling or stable algorithms and thus does not require that the variables to be normally distributed. The study concluded that the 4.0IR drivers have a moderate effect change on the management practice of road transport assets in Nigeria at the moment. The findings imply that management of road assets in Nigeria would moderately improve due to the 4.0IR technologies resulting in transport, safety and general efficiency and effectiveness of road networks in Nigeria. The study identified the 4.0IR drivers to include robotics, mobility, virtual and augmented reality, Internet of things and cloud computing, machine learning, artificial intelligence, blockchain, three-dimensional (3D) printing drones that are built with an attached 3D printer (the drone hangs a 3D printing nozzle that has fed plastic, concrete mix or other material from a tube connected to the top of the drone's printing path that precisely plotted by software, for a promised printing accuracy of 0.1 mm) and digital engineering. This study emanated from the government reports and past studies in the area of road transport asset management practice which the study investigated the major causes of poor practices and assessed the effect of the 4.0IR on the practice.
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Murugan, Reshma J., B. N. Bindhya, and G. S. Sreedaya. "Artificial intelligence - The promise for an agricultural revolution in new era." AGRICULTURE UPDATE 15, no. 4 (November 15, 2020): 435–37. http://dx.doi.org/10.15740/has/au/15.4/435-437.
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Agriculture is slowly becoming digital. The adoption of Artificial Intelligence (AI) and Machine Learning (ML) both in terms of agricultural products and in-field farming techniques are increasing. Artificial Intelligence in agriculture is emerging in three major areas, namely agricultural robotics, soil and crop monitoring and predictive analytics. The use of sensors and soil sampling techniques are increasing day by day which helps in gathering of data. In turn, this data is stored in farm management system which is better processed and analysed. Thus, the data available along with other related data paves a way to successfully deploy AI in agriculture. AI in agriculture is emergingin cognitive computing and it has all the scope to become the most disruptive technology in agriculture services as it is able to understand, learn and respond to different situations (based on learning) to increase efficiency. The areas where the use of cognitive solutions can benefit agriculture are growth driven by IOT, image-based insight generation, identification of optimal mix for agronomic products, health monitoring of crops and automation techniques in irrigation and enabling farmers. In addition, the drone based solutions have significant impact in terms of productivity gains, coping with adverse weather conditions, yield management and precision farming.The emergence of new age technologies like Artificial Intelligence (AI), Cloud Machine Learning, Satellite Imagery and advanced analytics are creating an ecosystem for smart farming. Fusion of all this technology is enabling farmers achieve higher average yield and better price control.
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Jha, BK, Anup Kumar, Shweta Kumari, and Neetu Kumari. "ICT application for promotion of integrated farming system." Oryza-An International Journal on Rice 60 (February 7, 2023): 71–77. http://dx.doi.org/10.35709/ory.2023.60.0.6.
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ICT is an umbrella term that includes communication devices like computer, mobile phone, radio, television, network hardware, satellite system etc. as well as services like audio and video call, text and multimedia messages. During first decade of twenty- first century, there had been spurt in experimentation of ICT in agriculture by the government, private, co-operative and non-government organizations (NGOs). The initiatives gave mixed result of success and failures. The initial challenges like lack of power back up, poor connectivity, high cost, lack of computer literacy and absence of digital content are disappearing at a faster rate. The growth in network infrastructure, cloud computing, decreasing price of computer and mobile phone and digital literacy have increased the internet access. The present-day initiatives involve multiple channels like web, mobile app, SMS and IVR in multiple languages. At the same time the gamut of information has been increasing from crop specific information to value chain information. The emergence of social media has opened new vista for agricultural extension through which two-way information in multimedia format can be exchanged at virtually no cost. These technologies can effectively be used for promotion of IFS. However, the response of research and extension system is not very encouraging. The extension professionals should gear up to develop technical competence and exposure so that content could be developed as per channel and in local language of the clients. The frontier technologies like sensor based diagnostic equipments, remote sensing and GIS, GPS technology as well as robotics and drone in agriculture are poised to change the landscape of agricultural extension.
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Botta, Alessio, Jonathan Cacace, Riccardo De Vivo, Bruno Siciliano, and Giorgio Ventre. "Networking for Cloud Robotics: The DewROS Platform and Its Application." Journal of Sensor and Actuator Networks 10, no. 2 (June 14, 2021): 34. http://dx.doi.org/10.3390/jsan10020034.
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With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewROS, a framework based on the Robot Operating System (ROS) which embodies the three-layer, Dew-Robotics architecture, where computation and storage can be distributed among the robot, the network devices close to it, and the Cloud. After presenting the design and implementation of DewROS, we show its application in a real use-case called SHERPA, which foresees a mixed ground and aerial robotic platform for search and rescue in an alpine environment. We used DewROS to analyze the video acquired by the drones in the Cloud and quickly spot signs of human beings in danger. We perform a wide experimental evaluation using different network technologies and Cloud services from Google and Amazon. We evaluated the impact of several variables on the performance of the system. Our results show that, for example, the video length has a minimal impact on the response time with respect to the video size. In addition, we show that the response time depends on the Round Trip Time (RTT) of the network connection when the video is already loaded into the Cloud provider side. Finally, we present a model of the annotation time that considers the RTT of the connection used to reach the Cloud, discussing results and insights into how to improve current Cloud Robotics applications.
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Ilori, Matthew Olusoji, and Ibrahim Ajagunna. "Re-imagining the future of education in the era of the fourth industrial revolution." Worldwide Hospitality and Tourism Themes 12, no. 1 (January 27, 2020): 3–12. http://dx.doi.org/10.1108/whatt-10-2019-0066.
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Purpose Globally, higher education has been, over the years, a source of innovation, policy, new knowledge and a national asset. However, the advent of the Fourth Industrial Revolution (4IR) is having an impact on the principles of learning from primary to tertiary levels. The purpose of this paper is to consider how the 4IR has and will continue to impact education at the various levels of learning. Design/methodology/approach The paper aims to bridge the perceived information gap and provide insights into the kinds of educational preparation and the skills and qualifications that 4IR jobs require. In response, the following are considered: the need to tweak the curriculum, adopt the right technology for in class and online delivery and the projection of other learning techniques and skills that are often not considered pertinent. Data gathering for the report was by discussion with experts and consultation of relevant articles and write-ups from related websites. Findings The advent of smart communication systems involving artificial intelligence, internet, robotics, virtual reality and digital textbooks has opened a new vista in relation to how and what is learnt in schools. Just as technologies brought about smart communication systems, the 4IR model of higher education is rapidly evolving and as such, curriculum development and review must be dynamic, and it must keep pace with the technological advances and skills required in the twenty first century. Research limitations/implications More purposeful research needs to be conducted in universities and industries with the intention of accelerating internal and external innovations so that markets can be expanded. Furthermore, efforts to reduce the cost and time of generating innovations will need to be intensified. Practical implications The value and emphasis that are placed on the acquisition of degrees and paper qualifications are changing rapidly. Although it is traditional for students to compete for admission to the face-to-face classroom model, it is no longer unusual for a student to take courses online from any part of the world and still be accepted into positions usually reserved for traditional classroom education. Social implications As at today, examples of 4IR services include Uber, Airbnb, Cloud services, Artificial intelligence, Cyber-security, three-dimensional printers, driverless cars and robotics. Machine learning and drone technology are also of growing significance. As yet, subjects dealing with such inventions and innovations are not part of the curriculum of many institutions and this is a cause for concern. Originality/value The 4IR era will bring great changes to how students are taught and what students must learn as the tools for transformational learning are already overwhelming. Jobs will be scarce for those without the requisite skills, whereas those with the right skills will have to keep up with the pace of technological development, otherwise they too will be left behind. Schools will increasingly become centres for the generation of innovation and its incubation and in all this, quality learning, teaching and knowledge impartation can easily be carried out online.
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Vázquez-Arellano, Manuel, David Reiser, Dimitrios Paraforos, Miguel Garrido-Izard, and Hans Griepentrog. "Leaf Area Estimation of Reconstructed Maize Plants Using a Time-of-Flight Camera Based on Different Scan Directions." Robotics 7, no. 4 (October 11, 2018): 63. http://dx.doi.org/10.3390/robotics7040063.
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The leaf area is an important plant parameter for plant status and crop yield. In this paper, a low-cost time-of-flight camera, the Kinect v2, was mounted on a robotic platform to acquire 3-D data of maize plants in a greenhouse. The robotic platform drove through the maize rows and acquired 3-D images that were later registered and stitched. Three different maize row reconstruction approaches were compared: reconstruct a crop row by merging point clouds generated from both sides of the row in both directions, merging point clouds scanned just from one side, and merging point clouds scanned from opposite directions of the row. The resulted point cloud was subsampled and rasterized, the normals were computed and re-oriented with a Fast Marching algorithm. The Poisson surface reconstruction was applied to the point cloud, and new vertices and faces generated by the algorithm were removed. The results showed that the approach of aligning and merging four point clouds per row and two point clouds scanned from the same side generated very similar average mean absolute percentage error of 8.8% and 7.8%, respectively. The worst error resulted from the two point clouds scanned from both sides in opposite directions with 32.3%.
Book chapters on the topic "Cloud robotics drone"
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Küfeoğlu, Sinan. "Emerging Technologies." In Emerging Technologies, 41–190. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07127-0_2.
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AbstractThis chapter presents brief descriptions and working principles of 34 emerging technologies which have market diffusion and are commercially available. Emerging technologies are the ones whose development and application areas are still expanding fast, and their technical and value potential is still largely unrealised. In alphabetical order, the emerging technologies that we list in this chapter are 3D printing, 5G, advanced materials, artificial intelligence, autonomous things, big data, biometrics, bioplastics, biotech and biomanufacturing, blockchain, carbon capture and storage, cellular agriculture, cloud computing, crowdfunding, cybersecurity, datahubs, digital twins, distributed computing, drones, edge computing, energy storage, flexible electronics and wearables, healthcare analytics, hydrogen, Internet of Behaviours, Internet of Things, natural language processing, quantum computing, recycling, robotic process automation, robotics, soilless farming, spatial computing and wireless power transfer.
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Saxena, Esha, Preety Shoran, and Meenakshi Yadav. "Smart Systems and Services by Artificial Intelligence Algorithms." In Applying Drone Technologies and Robotics for Agricultural Sustainability, 245–58. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6413-7.ch015.
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Artificial intelligence is facilitating the future of smart systems and their associated services. The world is witnessing the rapid growth in smart systems with artificial intelligence (AI) algorithms. Services must include a set of features to handle future trends, intelligent decisions, security, adaptivity, scalability, user-friendliness, time-saving ability, and adaptability to new architectural models. To satisfy these objectives, smart systems and services need advancements in working models of IoTs and applications of cloud computing. The AI and IoT create a great combination in various fields; health systems, agriculture, weather forecasting, manufacturing units, prediction, etc. Some of its applications include smart homes, smart cities, and smart businesses. This chapter also discuss about the role of IoT and cloud computing in smart systems, followed by smart city development, education system, environment protection, healthcare, water reservation, security, etc.
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Thomas, Lucia Agnes Beena. "Edge Cloud." In Advances in Computer and Electrical Engineering, 107–31. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-9023-1.ch008.
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With the proliferation of new technologies such as augmented and virtual reality, autonomous cars, 5G networks, drones, and IOT with smart cities, consumers of cloud computing are becoming the producers of data. Large volume of data is being produced at the edge of the network. This scenario insists the need for efficient real-time processing and communication at the network edge. Cloud capabilities must be distributed across the network to form an edge cloud, which places computing resources where the traffic is at the edge of the network. Edge cloud along with 5G services could also glint the next generation of robotic manufacturing. The anticipated low latency requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy are also inscribed by edge cloud. A number of giants like Nokia, AT&T, and Microsoft have emerged in the market to support edge cloud. This chapter wraps the features of edge cloud, the driving industries that are providing solutions, the use cases, benefits, and the challenges of edge cloud.
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Thomas, Lucia Agnes Beena. "Edge Cloud." In Research Anthology on Edge Computing Protocols, Applications, and Integration, 158–81. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5700-9.ch009.
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With the proliferation of new technologies such as augmented and virtual reality, autonomous cars, 5G networks, drones, and IOT with smart cities, consumers of cloud computing are becoming the producers of data. Large volume of data is being produced at the edge of the network. This scenario insists the need for efficient real-time processing and communication at the network edge. Cloud capabilities must be distributed across the network to form an edge cloud, which places computing resources where the traffic is at the edge of the network. Edge cloud along with 5G services could also glint the next generation of robotic manufacturing. The anticipated low latency requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy are also inscribed by edge cloud. A number of giants like Nokia, AT&T, and Microsoft have emerged in the market to support edge cloud. This chapter wraps the features of edge cloud, the driving industries that are providing solutions, the use cases, benefits, and the challenges of edge cloud.
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Raja, Ruthramathi, and Sivakumar Venkatachalam. "Factors Influencing the Adoption of Digital Technology in Transportation Among Logistics Service Providers." In Blockchain Applications in Cryptocurrency for Technological Evolution, 147–59. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6247-8.ch009.
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Digitalization is the use of digital technologies to change a business model and give new profit and value-producing openings; it's the development of moving to a digital business. Digital shipping refers to advanced operations that aim to give ground-breaking forces recounting dissimilar modes of transport and business procedure. Transportation technology points are to reuse and partake information that can prevent vehicle collisions, keep the industry moving, and reduce environmental impacts. Transportation is the association of material across the Earth's face by irrigating, wind, ice, or graveness. It includes the physical process of traction (dragging), suspense (being carried), and saltation (bouncing) and the chemical process of the result. Emerging technologies are technologies that are apparent as proficient in altering the status are robotics, artificial intelligence, drones, IoT, GPS, blockchain, cloud computing, etc. The objectives is to recognize the factor moving transportation costs and the application of digital technologies in the transport sector.
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Dix, Alan, Steve Gill, Jo Hare, and Devina Ramduny-Ellis. "Embodied Computation." In TouchIT, 378–405. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780198718581.003.0017.
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Abstract Computation itself seems immaterial, but whether on your smartphone or in ‘the cloud’, it is very physical: electrons moving on silicon wafer, photons streaming along optical fibres. This chapter explores this physicality of computation. Physics puts fundamental limitations on computation, and the chapter shows how this means that computation and information must come together at the same point in time and space. Practically, we have not reached these limits, Moore’s Law drives the miniaturization and commoditization of computation, which in turn enables radical changes including the Internet of Things and even coating every surface with a computation. In robots, autonomous vehicles, drones, and Alexa in the living room computation is physically amongst us. However, physical computation has been around for many years: the success of market economies is due to the physical representation of information in money, a role that is now changing with digital currency and online commerce.
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Sankaranarayanan, Suresh. "Applications of Artificial Intelligence for Smart Agriculture." In AI-Based Services for Smart Cities and Urban Infrastructure, 277–88. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5024-3.ch013.
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Smart cities is the latest buzzword towards bringing innovation, technology, and intelligence for meeting the demand of ever-growing population. Technologies like internet of things (IoT), artificial intelligence (AI), edge computing, big data, wireless communication are the main building blocks for smart city project initiatives. Now with the upcoming of latest technologies like IoT-enabled sensors, drones, and autonomous robots, they have their application in agriculture along with AI towards smart agriculture. In addition to traditional farming called outdoor farming, a lot of insights have gone with the advent of IoT technologies and artificial intelligence in indoor farming like hydroponics, aeroponics. Now along with IoT, artificial intelligence, big data, and analytics for smart city management towards smart agriculture, there is big trend towards fog/edge, which extends the cloud computing towards bandwidth, latency reduction. This chapter focuses on artificial intelligence in IoT-edge for smart agriculture.
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Akhtar, Mohammad. "Industry 4.0 Technologies Impact on Supply Chain Sustainability." In Supply Chain - Recent Advances and New Perspectives in the Industry 4.0 Era [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102978.
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A supply chain is a network that links technology, activities, resources and organisations involved in the manufacturing and distribution of product and services. Supply Chain Operations Reference model (SCOR) defines basic processes of the supply chain (SC) into five categories as Plan, Source, Make, Delivery and Return. The search for a more sustainable production and consumption system is so relevant today that the United Nations (UN) have selected it as one of their paramount societal objectives for sustainable development. The implementation of sustainability in production and consumption processes aims to mitigate negative pressures on the ecosystem generated by products, services, and transportation. Industry 4.0 (I40) technologies have sparked interest in recent years. The advanced digital technologies of I40 such as big data analytics (BDA), artificial intelligence (AI), machine learning (ML), internet of things (IoT) and sensors, block chain technology (BCT), robotic systems (RS), cloud computing (CC), cyber-physical system (CPS), additive manufacturing (AM) /3D printing (3D), virtual reality (VR), augmented reality (AR), autonomous vehicles (AV), and drones have found applications in many processes of manufacturing, logistics and SC. The benefits are sustainability, efficiency, cost reduction, transparency, traceability, and collaboration. In addition to benefits, I40 implementation is not free from challenges.
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Nawrocki, Miroslaw, Krzysztof Kurowski, and Radoslaw Gorzenski. "Cyber Space and Aviation 4.0 – New Testing Facilities for Next Generation of Cyber-Physical, Autonomous and Air Traffic Control Systems." In Modern Technologies Enabling Safe and Secure UAV Operation in Urban Airspace. IOS Press, 2021. http://dx.doi.org/10.3233/nicsp210008.
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Transforming basic multi-disciplinary research into applied research in the area of a new generation of networks, sensors, cyber-physical, and edge-cloud systems used for cyber space is a difficult task. However, moving even a step forward by providing advanced field and testing facilities for ground-air demonstrations for appearing Aviation 4.0 scenarios is a real challenge. In our opinion, such a rapid and dynamic process should be powered by many research and infrastructure projects. New development strategies are needed in the upcoming future to link emerging trends in information and communications technologies together with increased competitiveness and users expectations from fully autonomous drones, robots, cars, etc. This paper aims to share our early experiences in setting and providing distributed testbeds to cross different hardware, software, and cyber-physical components and pave the way for air-ground demonstrations of the new emerging IT paradigm – digital continuum. We also share our vision of implementing virtual and digital spaces at a large scale by the gradual transition towards higher levels of cyber-physical systems automation and autonomy. Finally, we promote dynamic, data-driven, service-oriented approaches and network-centric platforms for a new generation of air and ground control systems which will be validated in real conditions established thanks to our new airfield-based laboratories used in many ongoing and future R&D projects.
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Seely, Ron. "Small Newspapers." In A Field Guide for Science Writers. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195174991.003.0012.
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Some days, now that I have crested 50, I find myself surprised to be, of all things, a science reporter on a daily newspaper in a small but sophisticated city and immersed every day in a world of stem cells, radio-collared bald eagles, flakes of Martian meteorites, and strange deer diseases. I can't imagine a place I'd rather be at this point in my life, though sometimes the haphazard way I got here, the serendipitous nature of it all, makes my head spin—not to mention the fearful task of trying to make something called “proteomics” understandable for an audience that has maybe a minute and a half to read what I've written. After all, I made a terrible mess of the frog I was supposed to dissect in high school all those years ago. And trying to figure out exactly what Mendel was doing with all of those pea plants drove me nuts. Math? Well, suffice it to say that my problems with algebra and equations are what drove me to a career in journalism. Still, here I am, settled in Madison, Wisconsin, in the upper Midwest of America, carrying around business cards that identify me as science and environment reporter for the Wisconsin State Journal. In a recent, typical week, I researched and wrote a column about robotics, pounded out a quick news feature about why the human body gets cold in winter, made pesky phone calls to state officials about why they aren't enforcing the state's new pollution law, and churned out news briefs on everything from clouds of ionized hydrogen in the solar system to a pollution permit hearing for a local manufacturing plant. Between assignments, I had time to give a talk about science writing to a local high school biology class and to win one of the ongoing games of Scrabble in the cubicle at the newspaper where I make my workday home. Not a day goes by that I don't worry about losing this good job. That's because full-time science reporters on small to mid-sized daily newspapers in this country are an endangered species.
Conference papers on the topic "Cloud robotics drone"
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Alex, Chandykunju, and Aditya Vijaychandra. "Autonomous cloud based drone system for disaster response and mitigation." In 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA). IEEE, 2016. http://dx.doi.org/10.1109/raha.2016.7931889.
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Hwan Song, Seung, Hyun Wook Shon, Gyu Yang Yeon, and Hyouk Ryeol Choi. "Design and Implementation of Cloud-Like Soft Drone S-Cloud." In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018. http://dx.doi.org/10.1109/iros.2018.8593601.
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Blom, David, Ilya Berchenko, Farid Samie, and Darian Frajberg. "Shell Autonomous Integrity Recognition - Machine Vision Application for Inspections." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211838-ms.
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Abstract Shell Autonomous Integrity Recognition (AIR) on C3 AI Platform is an Artificial Intelligence (AI) application that allows pressure equipment and structural steel inspectors to quickly and easily make use of automated image capture and evaluation to support execution of external integrity inspections. By processing data in the cloud coming from inspections carried out with handheld devices, drones and robots, this application enables inspectors to objectively evaluate issues, identify items that may have been overlooked, reduce the time needed to generate reports, and improve inputs to maintenance planning. By using Shell Autonomous Integrity Recognition on C3 AI Platform, users can improve the quality, efficiency, and standardization of visual inspections.
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Maurell, Igor P., Caue Ferreira, Carlos A. Eguti, and Paulo Drews-Jr. "Geometric Primitive Fitting in Large Structure 3D Point Clouds Acquired by Drones." In 2021 Latin American Robotics Symposium (LARS), 2021 Brazilian Symposium on Robotics (SBR), and 2021 Workshop on Robotics in Education (WRE). IEEE, 2021. http://dx.doi.org/10.1109/lars/sbr/wre54079.2021.9605458.
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Medagoda, Lashika, Mitchell Galea, Suchet Bargoti, Junaid Khan, Toby Dunne, Steve Potiris, Zain Ul Abidin, et al. "Scalable Port Inspections Through Underwater, Terrestrial and Aerial Robotic Platforms." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/210999-ms.
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Abstract Asset management of a marine port or terminal requires inspection of the asset components below the water surface, at the water surface line and above the water surface. In order to determine asset health, high fidelity, multi-modal data is captured remotely using robotics, and subsequently analyzed. This facilitates the production of prioritized actionable insights to be produced. These insights can be scheduled as maintenance works. This paper outlines a novel multimodal inspection system that was deployed at a port to facilitate its remote inspection. Two inspections are detailed in this paper, with differing inspection requirements and constraints. The inspection operation can be broken down into multiple components, an underwater scan of the port, a water-surface scan, a ground level scan and an aerial scan. The Port Asset required the inspection of the wharf and quay walls. The Marine Terminal Asset required inspection of the complex pipework. The data collected from the different modalities were represented in the 3D space. The alignment of the different modalities could then be done in this representation. For the Port Asset, where multibeam sonar maps were collected, the difficulty in alignment of the different modalities is apparent due to no shared points below and under-water, which requires estimation using extended features as landmarks. There also exists slight warping between the data that must need localized scaling for certain sections, which may be done using local submaps and scaling. For the Marine Terminal Asset, artificial markers are used to allow scaling of the drone captured photogrammetry. High levels of coverage from the multiple views of the asset from different data collection strategies allowed the complex pipework to be well mapped, with further insights from the co-registered imagery. The novel information described in this paper is the unique combination of different modalities for a broadscale port inspection, with point clouds from sonar, lidar, photogrammetry and imagery, in a combined reference frame which acts as a digital twin for the port. This also allows unique insights, such as the exact context and magnitude of faults in the port environment, to allow corrective works to be targeted correctly.
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Al-Jadir, Sadik Jadir. "The Use of 5G Technologies in the Digital Transformation of the Oil/Gas Industry." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207529-ms.
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Abstract Many oil & gas companies embarked on their Digital Transformation (DX) journeys with rapid adoption of emerging digital technologies. Successful digital transformation initiatives are necessary for Oil/Gas Companies to improve efficiencies, streamline their operations and meet pressing challenges for cost reduction, increased efficiency, and improved safety. Oil & Gas fields and processing facilities require robust and reliable telecommunication infrastructure to support the application of much needed digital technologies. The availability of high-speed connectivity has been a challenge for many Oil/Gas companies operating in remote or hazardous locations. The latest Fifth Generation cellular technology (5 G) addresses such essential Oil/Gas requirements as increased speeds/bandwidths, very low network latencies, ultra-reliable communications, and the capacity to handle large number of users. 5G is designed around following technologies: Small (micro) cells requiring less power,Higher frequencies offering bigger data handling capacities,Cloud and Edge Computing for low network latencies and added security. These 5G design features will enable numerous Oil/Gas applications such as Industrial Robots/Drones, Virtual/Augmented Reality, Video Surveillance with Artificial Intelligence (AI) features (Face Recognition, Object Recognition & intelligent Image processing), Remote Asset Management, Industrial IoT communication between Sensors, Gateways and Device Controllers, Pipeline Leak Detection Systems, Telemetry and SCADA. 5G is therefore poised to be a key enabler in Digital Transformation. The UAE has an advanced telecom infrastructure that offers customers high speed fibre optic connectivity. UAE telecom operators have also been quick to deploy 5G in main cities. Etisalat for example is running a 5G pilot on Das Island with ADNOC Offshore and a major Network Supplier to test potential use cases of the technology in the O&G industry. The push for 5G in O&G will benefit from cooperation between the O&G industry, the telecom operators and technology providers. The role of Governments and the Telecom Regulators can further accelerate adoption through allocation of frequency spectrum to enable 5G Private Network model of deployment. The private network model is crucial for the Oil & Gas industry in view of the special requirements, nature and remoteness of oil and gas installations.
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Li, Jinman, Jianliang Zhou, Hongbo Huo, Shouwei Zhou, Yang Lin, and Linsong Cheng. "Pilot Construction of CNOOC Intelligent Oilfield for the Largest Offshore Oilfield in China." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22133-ms.
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Abstract Objectives/Scope In order to explore the benefits and potentials of digital transformation in China's offshore oilfields and improve the safety and efficiency of offshore oilfield's operations, China National Offshore Oil Corporation (CNOOC) has established a digital transformation pilot project in the Bohai Oilfield, which is not only the very first offshore digital transformation project but also the largest offshore oilfield in China. Integrating all aspects into one highly interactive system and utilizing the most advanced computational technologies, the pilot implementation provides seven modules to cover all aspects of field operations. Design, Technology and Implementation To meet the needs for less human operation, reservoir visualization, collaborative operation and robust decision-making for offshore field development and production, the pilot implementation of digital transformation at Bohai Oilfield includes three parts, 1) information system construction; 2) intelligent transformation of offshore platform equipment and facilities; and 3) the construction of a control center on shore. All the parts above are carried out through the V&V (verification and validation) method, get good controls of data, technology, process and organization. The first part is an information system construction, which applied new technology in big data, artificial intelligence, cloud computing, internet of things and micro service architecture. It provides improved functions of safety management, reservoir management, production optimization and mobile inspection. The second part is intelligent transformation of offshore platform equipment and facilities, such as utilization of drones, robotics, personal digital assistant, intelligent water injection pump and so on. The application of these intelligent equipment and facilities not only can collect much more data about for production and systems optimization, but also can emancipate the labor force. The third part is the construction of a control center on shore, which is the decision center of the whole oilfield. Linked with data lake and optical fiber cable, the control center can achieve remote control for the works on the platform. Expected Results and Benefits The whole pilot project has been executed from scratch and started operation in July 2021. With the digital transformation, the digital coverage rate for core business is 100%; Once the system runs smoothly per design, the offshore operators are expected to be reduced by 50% due to high level of automation; the equipment failure rate is expected to decrease by 20% due to more intelligent and thorough inspection and maintenance; the incident rate is expected to lower by 20% due to more intelligent QHSE management and high-level of automation; and the reservoir recovery rate is expected to increase by 5% due to optimized reservoir management and well operations. Novelty/Additional Information This pilot is the very first digital transformation trial in offshore China. The project team studied examples from many national and international companies and could not find anything that did what we wanted to do, which was to highly integrate every aspect of field operations into one intelligent system. The project team summoned resources from more than 30 companies, including leading service companies in the petroleum industry and IT and communication companies, 300 people, and started from the scratch to design a system that serves our purpose. Then the team implemented and tested all the modules, purchased, or developed all the hardware and devices, and started pilot operation of the system within 9 months from the project start. To the project team's knowledge, this highly integrated system might be a novel one in the industry. This will provide good experiences and lessons learned for the other 80 offshore oilfields in China. The design, implementation, proved technology, operation experience, etc., can be readily expanded to other fields shortly after the successful deployment of this pilot.