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%.
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Krus, Anne, Dirk van Apeldoorn, Constantino Valero, and Juan José Ramirez. "Acquiring Plant Features with Optical Sensing Devices in an Organic Strip-Cropping System." Agronomy 10, no. 2 (February 1, 2020): 197. http://dx.doi.org/10.3390/agronomy10020197.
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The SUREVEG project focuses on improvement of biodiversity and soil fertility in organic agriculture through strip-cropping systems. To counter the additional workforce a robotic tool is proposed. Within the project, a modular proof of concept (POC) version will be produced that will combine detection technologies with actuation on a single-plant level in the form of a robotic arm. This article focuses on the detection of crop characteristics through point clouds obtained with two lidars. Segregation in soil and plants was successfully achieved without the use of additional data from other sensor types, by calculating weighted sums, resulting in a dynamically obtained threshold criterion. This method was able to extract the vegetation from the point cloud in strips with varying vegetation coverage and sizes. The resulting vegetation clouds were compared to drone imagery, to prove they perfectly matched all green areas in said image. By dividing the remaining clouds of overlapping plants by means of the nominal planting distance, the number of plants, their volumes, and thereby the expected yields per row could be determined.
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Garg, P. K. "Characterisation of Fixed-Wing Versus Multirotors UAVs/Drones." Journal of Geomatics 16, no. 2 (October 31, 2022): 152–59. http://dx.doi.org/10.58825/jog.2022.16.2.44.
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Drones are Unmanned Aerial Vehicles (UAVs) that do not carry a human operator, fly remotely or autonomously, and carry lethal or non-lethal payloads. Advances in fabrication, navigation, remote control capabilities, and power storage systems have made possible the development of a wide range of drones. The most popular ones are fixed-wing and multirotor drones. They have several advantages and disadvantages and can be deployed quickly to obtain very high resolution imagery/point cloud data. With sophisticated computer vision, robotics and data, and low cost digital cameras, it is possible to get centimeter-level resolution and accuracy. Advances in technology have made the increased uses of drones for various applications. The uses of UAVs/drones are increasing allowing 2D and 3D maps to be created and used for creation of 3D maps and digital elevation models (DEMs). This paper describes in details about the two broad categories of UAVs; fixed-wing and multirotor UAVs. Their salient characteristics along with advantages and disadvantages are also given. It also provides insights to the users for selection of right kind of UAV.
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Samad, Tooba, Sohail Iqbal, Asad Waqar Malik, Omar Arif, and Peter Bloodsworth. "A multi-agent framework for cloud-based management of collaborative robots." International Journal of Advanced Robotic Systems 15, no. 4 (July 1, 2018): 172988141878507. http://dx.doi.org/10.1177/1729881418785073.
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This article presents a cloud-based multi-agent architecture for the intelligent management of aerial robots in a disaster response situation. In a disaster scenario, a team of highly maneuverable quadcopters is deployed to carry out surveillance and decision support in disaster-affected areas. In Pakistan, such events usually result from sudden unpredictable calamities such as earthquakes. The aim of this work is to develop a robust mechanism to autonomously manage and react to sensory inputs received in soft real time from an unstructured environment. The immediate goal is to locate the maximum number of trapped, injured people within a large area, and help first responders plan rescue activities accordingly. To evaluate the proposed framework, a number of simulations are carried out using GAMA platform to emulate a disaster environment. Subsequently, algorithms are developed to survey an affected geographical area through the use of small flight drones. The key challenges in this work are related to the combination of the domains of multi-agent technology, robotics, and cloud computing for effectively bridging the cyber world with the physical world. Therefore, the proposed work demonstrates the effective use of a limited number of drones to capture inputs from a disaster situation in the physical world, and such inputs are used for timely planning of rescue efforts. The results of fixed resource assignment are compared with the proposed reactive assignment strategy, and it clearly shows a significant improvement in terms of resource usage compared to traditional approach.
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Alsayed, Ahmad, and Mostafa R. A. Nabawy. "Indoor Stockpile Reconstruction Using Drone-Borne Actuated Single-Point LiDARs." Drones 6, no. 12 (November 29, 2022): 386. http://dx.doi.org/10.3390/drones6120386.
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A low-cost, yet accurate approach for stockpile volume estimation within confined storage spaces is presented. The novel approach relies on actuating a single-point light detecting and ranging (1D LiDAR) sensor using a micro servo motor onboard a drone. The collected LiDAR ranges are converted to a point cloud that allows the reconstruction of 3D stockpiles, hence calculating the volume under the reconstructed surface. The proposed approach was assessed via simulations of a wide range of mission operating conditions while mapping two different stockpile shapes within the Webots robotic simulator. The influences from modulating the drone flight trajectory, servo motion waveform, flight speed, and yawing speed on the mapping performance were all investigated. For simple rectangular trajectories, it was found that having longer trajectories that are adjacent to the storage walls provides best reconstruction results with reasonable energy consumption. On the other hand, for short rectangular trajectories within the storage middle space, the yawing speed at corners must be decreased to ensure good reconstruction quality, although this can lead to relatively high energy consumption. Comparing the volumetric error values, the average error from the proposed 1D LiDAR system, when operating at 6°·s−1 maximum yawing speed at the corners, was 0.8 ± 1.1%, as opposed to 1.8 ± 1.7%, and 0.9 ± 1.0% from the 2D and 3D LiDAR options, respectively. Moreover, compared to 2D and 3D LiDARs, the proposed system requires less scanning speed for data acquisition, is much lighter, and allows a substantial reduction in cost.
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Ghazal, Mohammed, Tasnim Basmaji, Maha Yaghi, Mohammad Alkhedher, Mohamed Mahmoud, and Ayman S. El-Baz. "Cloud-Based Monitoring of Thermal Anomalies in Industrial Environments Using AI and the Internet of Robotic Things." Sensors 20, no. 21 (November 7, 2020): 6348. http://dx.doi.org/10.3390/s20216348.
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Recent advancements in cloud computing, artificial intelligence, and the internet of things (IoT) create new opportunities for autonomous industrial environments monitoring. Nevertheless, detecting anomalies in harsh industrial settings remains challenging. This paper proposes an edge-fog-cloud architecture with mobile IoT edge nodes carried on autonomous robots for thermal anomalies detection in aluminum factories. We use companion drones as fog nodes to deliver first response services and a cloud back-end for thermal anomalies analysis. We also propose a self-driving deep learning architecture and a thermal anomalies detection and visualization algorithm. Our results show our robot surveyors are low-cost, deliver reduced response time, and more accurately detect anomalies compared to human surveyors or fixed IoT nodes monitoring the same industrial area. Our self-driving architecture has a root mean square error of 0.19 comparable to VGG-19 with a significantly reduced complexity and three times the frame rate at 60 frames per second. Our thermal to visual registration algorithm maximizes mutual information in the image-gradient domain while adapting to different resolutions and camera frame rates.
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Siripurapu, Sridhar, Naresh K. Darimireddy, Abdellah Chehri, Sridhar B., and Paramkusam A.V. "Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-II (Robotics, Drones, 3D-Printing, Internet of Things, Virtual/Augmented and Mixed Reality)." Electronics 12, no. 3 (January 20, 2023): 548. http://dx.doi.org/10.3390/electronics12030548.
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The substantial applicability of technological advancements to the healthcare sector and its allied segments are on the verge of questioning the abilities of hospitals, medical institutions, doctors and clinical pathologists in delivering world class healthcare facilities to the global patient community. Investigative works pertinent to the role played of technological advancements in the healthcare sector motivated this work to be undertaken. Part-I of the review addressed the applicable role play of advanced technologies such as Artificial intelligence, Big-data, Block chain, Open-Source and Cloud Computing Technologies, etc., to the healthcare sector and its allied segments. The current Part-II manuscript is critically focused upon reviewing the sustainable role of additional disrupting technologies such as Robotics, Drones, 3D-Printing, IoT, Virtual/Augmented/Mixed Reality, etc., to uncover the vast number of implicit problems encountered by the clinical community. Investigations governing the deployment of these technologies in various allied healthcare segments are highlighted in this manuscript. Subsequently, the unspoken challenges and remedial future directions are discussed thereof.
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Patel, Ujas, Sudeep Tanwar, and Anuja Nair. "Performance Analysis of Video On-demand and Live Video Streaming using Cloud based Services." Scalable Computing: Practice and Experience 21, no. 3 (August 1, 2020): 479–96. http://dx.doi.org/10.12694/scpe.v21i3.1764.
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The advent of Cyber-Physical Systems (CPS) has brought a revolutionary change coined as a mixture of information, communication, computation, and control. With applications in smart grid, health monitoring, automatic avionics, distributed robotics, etc., CPS is currently an area of attention among the academia and industry. The advancement of mobile communications and embedded technology has made it possible to build large scale CPS consisting of the interconnection of mobile phones. These devices collect information about the surrounding environment at any time anywhere basis through real-time video capture. Video streaming has proven to be a massive industry that is growing rapidly playing an important role in everyday life. Customer-driven approach wanting best experience with quality has to be the core offering of contemporary scenario. Video streaming is categorized into Video-On-Demand Streaming (VoDS) and Live Video Streaming (LVS) showing the current state-of-art opportunities. Many diverse applications of video streaming are military video surveillance using drones, live sports match player face recognition, on-demand video characters recognition, movie summarization like identifying parts of the movie which are viewed many times by different users, movie and series recognition, motion detection, gesture recognition, image segmentation, etc. This paper introduces an approach to develop video analysis on VoD and LVS using cloud-based services and analyzes the impact of Quality of Experience (QoE), cost, and bandwidth on the cloud. To achieve the best user experience for video streaming and video analysis, Content Delivery Network (CDN) offers the best QoE at various analyzed locations using various cloud providers like Amazon Web Services (AWS) CloudFront, Google Cloud CDN, Azure CDN, Akamai CDN, etc.
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Singh, Devendra, Rajesh Singh, Anita Gehlot, Shaik Vaseem Akram, Neeraj Priyadarshi, and Bhekisipho Twala. "An Imperative Role of Digitalization in Monitoring Cattle Health for Sustainability." Electronics 11, no. 17 (August 29, 2022): 2702. http://dx.doi.org/10.3390/electronics11172702.
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In the current context, monitoring cattle health is critical for producing abundant milk to satisfy population growth demand and also for attaining sustainability. Traditional methods associated with cattle health must be strengthened in order to overcome the concern of detecting diseases based on the health condition. This problem has moved attention toward digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), cloud computing, edge/fog computing, big data, blockchain, drones, robotics, and augmented reality (AR)/virtual reality (VR), as these technologies have proved for real-time monitoring, intelligent analytics, secure data distribution, and real-time visual experience. The purpose of this study is to examine and discuss many cattle health disorders, as well as to address the fundamental notion of digital technologies, as well as the significance of these technologies for cattle health. Furthermore, the article addressed the different devices that integrated IoT and AI for cattle health monitoring, in which the previous architecture of cattle health monitoring is presented. Based on the review, the article discusses the challenges and suggests recommendations that can be implemented for the future work
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Choudhari, C. S., and D. Y. Dhande. "Smart Technologies to Mitigate and Manage The Pandemic: Today and Tomorrow." SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology 13, no. 02 (December 25, 2021): 82–86. http://dx.doi.org/10.18090/samriddhi.v13i02.4.
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COVID 19 pandemic has affected the modern world in an unimaginable way. Outbreak of the coronavirus and months long total lockdown in major parts of the world has highlighted the lacunas in disaster management and unpreparedness of the world for such a type of pandemic and “unexpected” future pandemic. All the efforts put in combating this infectious virus and to deal with adverse effects of pandemic has proved that use of technology is the only and would be the only effective solution. Each and every sector including the health sector has no option other than adoption of newer technologies in innovative engineering ways. This paper tries to suggest use of various technologies including Artificial Intelligence (AI), cloud computing, big data, blockchain, 5G and smart applications, Internet of Things (IoT), drones, robotics. These and few more digital technologies have been playing a crucial role in effective management of pandemic. This focussed review and discussion is expected to create awareness and motivation to the health care sector for using all the major Industry 4.0 technologies leading to Medicine 4.0. This technological revolution in healthcare and allied sectors will help in effective management of pandemic.
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Wang, J., and M. Shahbazi. "MAPPING QUALITY EVALUATION OF MONOCULAR SLAM SOLUTIONS FOR MICRO AERIAL VEHICLES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (November 29, 2019): 413–20. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w17-413-2019.
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Abstract. Monocular simultaneous localization and mapping (SLAM) attracted much attention in the mobile-robotics domain over the past decades along with the advancements of small-format, consumer-grade digital cameras. This is especially the case for micro air vehicles (MAV) due to their payload and power limitations. The quality of global 3D reconstruction by SLAM solutions is a critical factor in occupancy-grid mapping, obstacle avoidance, and map representation. Although several benchmarks have been created in the past to evaluate the quality of vision-based localization and trajectory-estimation, the quality of mapping products has been rarely studied. This paper evaluates the quality of three state-of-the-art open-source monocular SLAM solutions including LSD-SLAM, ORB-SLAM, and LDSO in terms of the geometric accuracy of the global mapping. Since there is no ground-truth information of the testing environment in existing visual SLAM benchmark datasets (e.g., EuRoC, TUM, and KITTI), an evaluation dataset using a quadcopter and a terrestrial laser scanner is created in this work. The dataset is composed of the image data extracted from the recorded videos by flying a drone in the test environment and the high-fidelity point clouds of the test area acquired by a terrestrial laser scanner as the ground truth reference. The mapping quality evaluation of the three SLAM algorithms was mainly conducted on geometric accuracy comparisons by calculating the deviation distance between each SLAM-derived point clouds and the laser-scanned reference. The mapping quality was also discussed with respect to their noise levels as well as further applications.
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Bongomin, Ocident, Aregawi Yemane, Brendah Kembabazi, Clement Malanda, Mwewa Chikonkolo Mwape, Nonsikelelo Sheron Mpofu, and Dan Tigalana. "Industry 4.0 Disruption and Its Neologisms in Major Industrial Sectors: A State of the Art." Journal of Engineering 2020 (October 10, 2020): 1–45. http://dx.doi.org/10.1155/2020/8090521.
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Very well into the dawn of the fourth industrial revolution (industry 4.0), humankind can hardly distinguish between what is artificial and what is natural (e.g., man-made virus and natural virus). Thus, the level of discombobulation among people, companies, or countries is indeed unprecedented. The fact that industry 4.0 is explosively disrupting or retrofitting each and every industrial sector makes industry 4.0 the famous buzzword amongst researchers today. However, the insight of industry 4.0 disruption into the industrial sectors remains ill-defined in both academic and nonacademic literature. The present study aimed at identifying industry 4.0 neologisms, understanding the industry 4.0 disruption and illustrating the disruptive technology convergence in the major industrial sectors. A total of 99 neologisms of industry 4.0 were identified. Industry 4.0 disruption in the education industry (education 4.0), energy industry (energy 4.0), agriculture industry (agriculture 4.0), healthcare industry (healthcare 4.0), and logistics industry (logistics 4.0) was described. The convergence of 12 disruptive technologies including 3D printing, artificial intelligence, augmented reality, big data, blockchain, cloud computing, drones, Internet of Things, nanotechnology, robotics, simulation, and synthetic biology in agriculture, healthcare, and logistics industries was illustrated. The study divulged the need for extensive research to expand the application areas of the disruptive technologies in the industrial sectors.
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Saibani, Nizaroyani, Jaharah A. Ghani, Muhammad Hassan Shamsul Akmar, Wa Kai Boon, Mohan Raj Ravi, Muhammad Azim Md Nawawi, and Nur Aziatul Izwa Mohd Asri. "Latest Advancement of Technologies in Supply Chain Management: An Overview." Jurnal Kejuruteraan 33, no. 4 (November 30, 2021): 785–91. http://dx.doi.org/10.17576/jkukm-2021-33(4)-01.
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Supply chain management (SCM) involves an interconnected structure of facilities that produces elements or compounds for transforming into a semifinished compound. After completion, the final compound is delivered to customers via a distribution system. Owing to ever-changing customer demands, increasingly efficient and resilient SCM is necessary, which requires support from the latest technologies. Therefore, this paper presents an overview of the latest technologies in SCM and logistics. The management of a supply chain and role of the different actors involved differ from industry to industry and company to company. Consequently, SCM has become a crucial issue to manufacturers, professionals and researchers. The latest technologies identified in this paper include radio frequency identification, vehicular ad hoc networks, the Internet of things, robotics and artificial intelligence and blockchain. Moreover, the application of the aforementioned technologies in different industries and systems is discussed to understand how the technologies impact practitioners. Although not discussed thoroughly, other recent technology trends in SCM and logistics, such as machine learning, autonomous vehicles/drones, advanced analytics, cloud logistics, supergrid logistics, anticipatory logistics, omnichannel logistics and additive manufacturing (3D printing), are also highlighted in this paper. By understanding the advancements in SCM technology, the possible direction of future innovations can be effectively planned and articulated.
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Ryvak, Nataliya O. "World trends in the market of mechanical engineering." Socio-Economic Problems of the Modern Period of Ukraine, no. 5(151) (2021): 37–43. http://dx.doi.org/10.36818/2071-4653-2021-5-5.
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The article analyzes the main trends in the global market of mechanical engineering, in particular, in the branches of agricultural engineering, mechanical engineering for light industry, construction and road engineering, and energy engineering. It also addresses the structure and development trends of the mechanical engineering market by regions, changes in the business environment of the mechanical engineering industry, the impact of the Covid-19 pandemic on the state and development of the global mechanical engineering market, new rules and requirements for manufacturers of mechanical engineering products, and technological innovations and trends. Mechanical engineering companies today are at the epicenter of technological transformation. The mechanical engineering industry creates individual digital capabilities and intelligently combined products. Innovative processes such as related production, forecast service and innovative service models are increasingly used in mechanical engineering. The use of modern digital technologies in mechanical engineering is becoming a necessity that prevents the risks of losing relevance in the market of modern industry. Although the basic principles of mechanical engineering, such as thermodynamics, fluid mechanics and machine design, still remain in force, the latest technologies are contributing to the rapid development of composites, mechatronics and nanotechnology. These new subject areas, which are the result of modern achievements, have become a prerequisite for the development of new and promising industries, including artificial intelligence and biomechatronics. The growing demand for increased production efficiency while minimizing operating costs has led to demand for new and innovative technologies. Based on the study of the introduction of new technologies in mechanical engineering and global trends in the industry, the author substantiates the feasibility of accepting the need for globalization in mechanical engineering as a new norm, taking into account costs, tax consequences, quality and delivery in planning the existing geographical location, supply chains, strategic partnerships; reduction of the general supply cycle for better adaptation to the changing environment; optimization of existing production facilities, automation and attraction of advanced digital technologies for the establishment of work processes; implementation of advanced technologies in mechanical engineering, such as artificial intelligence, Internet of Things, nanoengineering, advanced data analytics, automation of robotic processes, blockchain, robotics, cloud computing augmented reality, 3D printing, drones, 5G, etc.; raising the qualification level of mechanical engineering workers.
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Singh, Rajat, Rajesh Singh, Anita Gehlot, Shaik Vaseem Akram, Neeraj Priyadarshi, and Bhekisipho Twala. "Horticulture 4.0: Adoption of Industry 4.0 Technologies in Horticulture for Meeting Sustainable Farming." Applied Sciences 12, no. 24 (December 8, 2022): 12557. http://dx.doi.org/10.3390/app122412557.
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The United Nations emphasized a significant agenda on reducing hunger and protein malnutrition as well as micronutrient (vitamins and minerals) malnutrition, which is estimated to affect the health of up to two billion people. The UN also recognized this need through Sustainable Development Goals (SDG 2 and SDG 12) to end hunger and foster sustainable agriculture by enhancing the production and consumption of fruits and vegetables. Previous studies only stressed the various issues in horticulture with regard to industries, but they did not emphasize the centrality of Industry 4.0 technologies for confronting the diverse issues in horticulture, from production to marketing in the context of sustainability. The current study addresses the significance and application of Industry 4.0 technologies such as the Internet of Things, cloud computing, artificial intelligence, blockchain, and big data for horticulture in enhancing traditional practices for disease detection, irrigation management, fertilizer management, maturity identification, marketing, and supply chain, soil fertility, and weather patterns at pre-harvest, harvest, and post-harvest. On the basis of analysis, the article identifies challenges and suggests a few vital recommendations for future work. In horticulture settings, robotics, drones with vision technology and AI for the detection of pests, weeds, plant diseases, and malnutrition, and edge-computing portable devices that can be developed with IoT and AI for predicting and estimating crop diseases are vital recommendations suggested in the study.
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Connolly, Aidan J. "86 Reaching Genetic Potential in Pigs: 10 Disruptive Digital Technologies." Journal of Animal Science 100, Supplement_2 (April 12, 2022): 206. http://dx.doi.org/10.1093/jas/skac064.349.
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Abstract Consumer (‘prosumer’) concerns over animal welfare and the environmental footprint of pork production dominate the media. Indeed, the discussion of alternatives to pork, both from the continued global growth in chicken consumption and advances in cellular meat production and vegetable protein alternatives, represent real threats to pork’s future. Producers and processors continue to focus genetic improvement, nutrition, and management to improve meat production efficiency. Disease mitigation and animal health limit our ability to reach the pigs genetic potential, either in terms of pigs processed per sow, or breaching the 2:1 lifetime feed conversion. Can farmers continue to gain more pigs per sow, while keeping them healthy and alive? How do we maximize meat yield per carcass without losing flavor and the consumer experience? Are there limits to how low we can go in the conversion of nutrients into feed? Despite increased consumer demands and the continued need to improve production efficiency, the management of pigs has changed little in the last decades, often relying on decades old innovations and enhanced biosecurity. Innovations such as vertical hog farms in China, muti site production, and new feed technologies offer incremental but not disruptive improvements. The 10 digital technologies (PWC) is a useful framework to review the technologies with the potential to transform swine production. These are 3D Printing, Internet of Things, Artificial Intelligence, Data Analytics, Cloud Computing, Robotics, Drones, Blockchain, Virtual Reality and Augmented Reality (‘Metaverse’). Concepts such as precision nutrition, precision management recognize the need for better data, and data underpins advances such as nutrigenomics, microbiota and the environment of the pig. Digital technologies can disrupt pork production while offering the opportunity to respond to consumers, legislators, producer demands and other actors within the pork production chain.
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Mahajan, Ar Gayatri. "Swift Rising Pattern of New Emerging Construction Technology Trends in the Construction Industry." International Journal of Innovative Technology and Exploring Engineering 11, no. 11 (October 30, 2022): 55–64. http://dx.doi.org/10.35940/ijitee.g9236.10111122.
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Construction technology is a collective term for types of technology that have a specific use within the construction industry. Adoption of recent digital transformation technology is the need of today to speed up the business and is also the basis of construction improvement. Incorporating and practicing the technologies such as cloud-based communication and collaboration solution, Mobile Apps and 5G,3D printing, Building Information Modelling (BIM) and Digital Twins, CAD / CAM, Augmented Reality(AR)/ Virtual Reality(VR), Big Data, Internet of Things(IoT), Wearables, Blockchain(BC), Modular Construction(MC), Offsite Manifesting, Prefabrication(PF), Robotic, Drones and Global Positioning System (GPS) controlled equipment expedite the progress in the Construction industry (CI). Resources used are journaled research articles, web/net surfing, books, thesis, reports/surveys, magazines, etc. The outline of the research organization for this study is framed at four distinct levels in context to conceptualization, resources, innovative and emerging trends in CI, and better methods for completion of the construction projects. The present study conducted during 2020-2022 reveals that implementing these technologies improves the level of standards, planning, security, well-being, sustainability, and economics too. Application uses, benefits, impact, advantages/disadvantages, limitations and challenges, and policies are dealt with to provide information to architects and builders for smooth completion of the project. Results explain that construction technology trends vary from 4 to 15 for CI, and eventually, it reaches 27 for Civil Engineering (CE). The perspective of the most recent innovations, trends, tools, challenges, and solutions is highly embraced in the field of construction. The incorporation of the above said technologies in the pandemic Covid -19and post-pandemic might lead to a focus on finding out effective ways to adopt new-age technologies for CI.
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Trushkina, N., H. Dzwigol, O. Serhieieva, and Yu Shkrygun. "Development of the Logistics 4.0 Concept in the Digital Economy." Economic Herald of the Donbas, no. 4 (62) (2020): 85–96. http://dx.doi.org/10.12958/1817-3772-2020-4(62)-85-96.
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The transition to a digital economy is becoming a key driver of GDP growth. This is due not only to the effect obtained from the automation of existing processes, but also from the introduction of new, breakthrough business models and technologies, including digital platforms, digital ecosystems, in-depth analytics of big data, Industry 4.0, Logistics 4.0. At the same time, digital transformation is seen as a radical change in the complex of business processes, from product development to customer service, as well as the introduction of modern digital technologies in the organization of business processes in enterprises. The purpose of the article is to analysis the features and trends of organizing logistics activities in the context of digital transformation of business processes; research of the main prerequisites for the formation of the Logistics 4.0 concept; determination of priority directions for its further development in the context of Industry 4.0. Based on the generalization of scientific approaches, the definition of the concept of "Logistics 4.0" has been clarified, which means the modern paradigm of managing logistic (material, financial, information, transport) flows and organizing a complex of logistics activities (purchase and delivery of material resources, warehousing, production, stock formation, recycling of industrial waste, customer service, transportation and sale of finished products) using breakthrough digital technologies and information systems. The priority areas of organizing the logistics activities of enterprises using digital technologies include the following: multichannel logistics; logistics marketplaces; rethinking the use of packaging; mass personalization; Silver Economy (new services for older clients and new opportunities for older workers); sustainable logistics; sharing economy; multi-supply; customer experience; smart containerization; big data analytics; augmented and virtual reality; cloud service applications and APIs; Internet of Things; robotics and automation; new generation wireless communication; blockchain; Artificial Intelligence; unmanned aerial vehicles or "drones"; 3D printing; unmanned vehicles; quantum computing; supergrid logistics; space logistics; the use of digital platforms that unite customers and transport and logistics companies (the parties can enter into digital contracts, exchange transport booking requests and electronic documents, control the delivery of goods in real time). All this can help to reduce costs by optimizing procurement; decrease in personnel costs and decrease in labour costs as a result of automation; reduction of errors in logistics; optimization of the supply process; efficient warehouse management; forecasting shipments; creation of optimal routes; operational planning of loads and control of delivery times; ensuring product delivery on time, improving customer loyalty; optimal interaction with customers on the "last mile".
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Lytvynenko, O. "New requirements for technical acceptability of construction products as a component of the construction quality assurance system." Ways to Improve Construction Efficiency 1, no. 47 (January 29, 2021): 108–18. http://dx.doi.org/10.32347/2707-501x.2021.47(1).108-118.
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The analysis and generalization of theoretical approaches to the formation of the construction quality system, the generalization of the legislative and regulatory framework for quality control in construction. Analysis of the theoretical prerequisites for the formation of quality control of construction revealed that the digital transformation of construction is an integral part of the development of modern society, a prerequisite for changing the system of construction, including control, quality assurance and evaluation of construction processes, works, materials, products and structures.
It was found that the quality in construction is directly affected by the following factors: quality and completeness of design documentation; the possibility and obligation to comply with legal requirements; quality of construction processes and works, strict compliance with the requirements of technology and construction organization; quality of construction products and structures; technical ability to provide a given level of quality with the help of machines, mechanisms, means of small mechanization, etc .; the level of qualification of management staff, workers and line ITP. The quality system itself can be presented in the format of a "black box", where the factor will be named at the entrance, and at the exit - buildings and structures that meet a given level of quality throughout the life cycle of the object.
It is proposed to consider the construction quality management system in the form of a multicomponent formation and at the same time a dynamic environment, which is constantly changing under the influence of external and internal factors and has a high degree of scholasticism and uncertainty. With the introduction of digital technologies in the organization of construction, including VIM modeling, use of artificial intelligence, cloud services for information storage, quality control tools that can be performed without human intervention, such as drones, robotic elements, surveillance cameras and others, the construction quality assurance system has to change, taking into account the realities of time. Therefore, the system of quality formation in the article is proposed to be considered throughout the life cycle of the object - from pre-project research to liquidation. This will, in contrast to existing approaches, not only combine into a single system all the components of assurance, evaluation and quality control, which are used at the level of all participants in the construction, but also to ensure integrated process management.
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Ullah, Fahim, Samad Sepasgozar, and Changxin Wang. "A Systematic Review of Smart Real Estate Technology: Drivers of, and Barriers to, the Use of Digital Disruptive Technologies and Online Platforms." Sustainability 10, no. 9 (September 3, 2018): 3142. http://dx.doi.org/10.3390/su10093142.
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Real estate needs to improve its adoption of disruptive technologies to move from traditional to smart real estate (SRE). This study reviews the adoption of disruptive technologies in real estate. It covers the applications of nine such technologies, hereby referred to as the Big9. These are: drones, the internet of things (IoT), clouds, software as a service (SaaS), big data, 3D scanning, wearable technologies, virtual and augmented realities (VR and AR), and artificial intelligence (AI) and robotics. The Big9 are examined in terms of their application to real estate and how they can furnish consumers with the kind of information that can avert regrets. The review is based on 213 published articles. The compiled results show the state of each technology’s practice and usage in real estate. This review also surveys dissemination mechanisms, including smartphone technology, websites and social media-based online platforms, as well as the core components of SRE: sustainability, innovative technology and user centredness. It identifies four key real estate stakeholders—consumers, agents and associations, government and regulatory authorities, and complementary industries—and their needs, such as buying or selling property, profits, taxes, business and/or other factors. Interactions between these stakeholders are highlighted, and the specific needs that various technologies address are tabulated in the form of a what, who and how analysis to highlight the impact that the technologies have on key stakeholders. Finally, stakeholder needs as identified in the previous steps are matched theoretically with six extensions of the traditionally accepted technology adoption model (TAM), paving the way for a smoother transition to technology-based benefits for consumers. The findings pertinent to the Big9 technologies in the form of opportunities, potential losses and exploitation levels (OPLEL) analyses highlight the potential utilisation of each technology for addressing consumers’ needs and minimizing their regrets. Additionally, the tabulated findings in the form of what, how and who links the Big9 technologies to core consumers’ needs and provides a list of resources needed to ensure proper information dissemination to the stakeholders. Such high-quality information can bridge the gap between real estate consumers and other stakeholders and raise the state of the industry to a level where its consumers have fewer or no regrets. The study, being the first to explore real estate technologies, is limited by the number of research publications on the SRE technologies that has been compensated through incorporation of online reports.
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Luntovskyy, Andriy. "MODERN APPS AND PLATFORMS FOR THE ROBOTS." Visnyk Universytetu “Ukraina”, 2019. http://dx.doi.org/10.36994/2707-4110-2019-1-22-02.
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Nowadays, the number of robots that co-operate with the humans, machines and with each other in various fields of manufacturing and economics, everyday life, entertainment industry, social pedagogy is growing rapidly.Server-free mobile additions are widely used in robotics: applications that are built directly into the actuators and mechanisms; Cloud-oriented applications and others.As a result of the shifted emphasis on performance, energy and algorithms efficiency of addition and platforms for robotics in the future will develop with optimization of the following algorithms: unlimited movements of the robot and its orientation in 3D space; Detection of collisions of robot body (autonomous relative location) with prevention of dead end situation; Routing of autonomous ride and flight for unmanned devices, auto and drone in.ROS (Robot Operating System) for personal robots - known robotics platform today popular in industry and academic institutions. ROS includes the following architectural components: Package Management components; Abstract layer for hardware and hardware (Hardware Abstraction Layer) and device drivers; components with communication and messaging functions between Middleware programs or parts and Websites.Swarm works can be programmed to simulate 2d-forms, which are inherent in flocks of insects, fish, and birds. Researchers have managed to provide Swarm with their own coordination, which forms a significant step in the development of collective artificial intelligence Hundreds of robots cooperate in the field of cleaning the environment from the consequences of natural disaster, others model social processes.The paper is dedicated to the important scientific-practical problem of the use of modern mobile serverless apps, which are capable to autonomous operation, and robotics supporting platforms, in particular, to their classification and standardization. The scenarios for the use of robots that focus not only on manufacturing and modeling processes in the industry but also for behavioral modeling, amomg them on the use of robots in pedagogy and sociology, are considered.
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Nikitenko, Kateryna, and Hanna Zhosan. "DETERMINING THE ROLE OF BIG DATA IN DECISION-MAKING IN THE ECONOMY AND FINANCE." Economic scope, 2020. http://dx.doi.org/10.32782/2224-6282/161-11.
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Consulting agency PricewaterhouseCoopers has identified eight key technologies for the digital economy: the Internet of Things and artificial intelligence - the foundation for a new generation of digital resources; robotics, drones and 3D printers - devices that help transfer the capabilities of a computer to the material world; virtual reality is also augmented - technologies that combine the physical and digital worlds; blockchain and cloud computing - a new approach to basic business accounting operations. Analysis of recent research and publications. The topic of big data is still controversial, although it is being studied by specialists in various fields (economics, information technology, politics, and others). The influence of big data on social processes and business organization, in particular, was studied by Bill Franks, Victor Mayer-Schonberger, Kenneth Kukier, Eric Siegel, John Foreman and others. Publicistic materials prevail among domestic sources, but there is a lack of fundamental works in this direction. Purpose of the article. explore the essence and practical application of revolutionary digital technologies - cloud computing, big data and the Internet of things. The article identifies the advantages and disadvantages of cloud technologies, forms a model of cloud services, discusses technologies for working with big data, analyzes the results of a Tech Pro Research survey on the use of big data, and builds a technological ecosystem of the Internet of Things. Digitization is already a reality, and the penetration of the Internet and digital technologies into traditional industries has become one of the main trends in recent years and is taking place on a global scale, which allows us to talk about the digital transformation of all sectors of the economy, social life and the formation of a new economic structure - the digital economy. The practical use of digital economy technologies is a modern trend in the socio-economic life of a modern state, actively influences consumer behavior, manifests itself in mobility and the desire of companies for continuous improvement.
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Jarial, Sapna. "Internet of Things application in Indian agriculture, challenges and effect on the extension advisory services – a review." Journal of Agribusiness in Developing and Emerging Economies, January 20, 2022. http://dx.doi.org/10.1108/jadee-05-2021-0121.
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Purpose The emerging technologies of the Fourth Industrial Revolution are transforming various industries, including agriculture. Unaware, young male and female farmers leave the agriculture profession as they perform unsustainable practices. Precision agriculture using the Internet of Things (IoT) is a solution to sustainable agriculture. Extension professionals are at the heart of disseminating agricultural advisory agricultural services in India. The discourse on the IoT is entering the space of extension advisory services (EASs) and social sciences. Thus, the present paper seeks to review the application of IoT in Indian agriculture, its challenges and its effect on EASs. The conceptual framework is drawn from disruptive and surveillance capitalist theories. Design/methodology/approach Online literature review was conducted on electronic e-book Ebsco, Google scholar, PubMed, Jane, j gate, research4life, springer journal and Mendeley databases for full-text repositories, textbook, thesis, web articles, newspaper articles, reports, blogs for the year 1990 to May 2021 using keywords “IoT application in agriculture,” “emerging technologies in agriculture,” “challenges in IoT application,” “extension advisory services sources of information,” “big data and extension advisory, “IoT and extension advisory in India.” Only publications in the English language were included. Findings IoT aids progressive farmers and small farmers alike. Drones, robotics, precision irrigation, livestock tracking and crop disease surveillance are examples of IoT applications in agriculture. Only large corporations and governments access IoT, and for them, big data storage is an issue. Privacy and security concerns demand upgrades in IoT systems. Solutions to the convergence of IoT with the cloud will leverage agricultural EASs, resulting in fast computing, precise and proactive up-to-date problem solving. Hence, the need for communication between firms and clients has ceased. Thus, the jobs of extension agents are replaced. Research limitations/implications The competence of future human extension agents lies in reskilling as a “knowledge broker” of relationships and expertise, as s/he cannot have all multidisciplinary knowledge. Originality/value Although IoT applications in agriculture are available from a technological standpoint, there remains an awareness gap regarding the impact of IoT applications in agricultural EASs. This study will aid in a better comprehension of IoT applications from current and prospective EASs.
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Mukherjee, Arijit, Jayeeta Mondal, and Swarnava Dey. "Accelerated Fire Detection and Localization at Edge." ACM Transactions on Embedded Computing Systems, January 26, 2022. http://dx.doi.org/10.1145/3510027.
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Fire-related incidents continue to be reported as a leading cause of life and property destruction. Automated fire detection and localization (AFDL) systems have grown in importance with the evolution of applied robotics, especially because use of robots in disaster situations can lead to avoidance of human fatality. The importance of AFDL on resource-constrained devices has further grown, as most unmanned vehicles (drones or ground vehicles) are battery operated with limited computational capacity, the disaster situations cannot guarantee uninterrupted communication with high end resources in the cloud, and yet faster response time is a prime necessity. Traditional computer-vision based techniques require hand-engineered features on a case-by-case basis. Deep Learning -based classifiers perform well for fire/no-fire classification due to the availability of large datasets for training, however, a dearth of good fire localization datasets renders the localization performance below par. We have tried to address both problems with a multi-task learned cascaded model that triggers localization workflow only if the presence of fire is detected, through a strong classifier trained on available large fire datasets. This presents only fire images to a relatively weaker localization model, reducing false positives, false negatives, and thereby improving overall AFDL accuracy. The multi-task learning (MTL) approach for end-to-end training of a stitched classifier and object localizer model on diverse datasets enabled us to build a strong fire classifier and feature extractor. It also resulted in a single unified model, capable of running on “on-board” compute infrastructure without compromising on accuracy. To achieve the target inference rate for the AFDL deployment, we have investigated the effect of quantization and compression due to hardware acceleration on an MTL model. This paper presents an approach to automate the hardware-software co-design to find the optimum parameter partitioning for a given MTL problem, especially when some parts of the model are hardware accelerated. We present combined evaluation results showing that our methodology and the corresponding AFDL model strikes a balance between the frames inferred per second and several accuracy metrics. We report fire localization accuracy in terms of mean average precision (object detection), that is not done earlier for embedded AFDL systems.