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Internet of Things in the Field of smart Farming: Benefits and Challenges 7

Internet of Things in the Field of Smart Farming: Benefits a...

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7th international conference on ICT for smart Society, ICISS 2020

作者： Dewangga A, Pratama Suhono H, Supangkat Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781665404228

The increase in population at the global level results in an increase in food demand and a shift towards smart agricultural practices. This is supported by the reduced availability of agricultural land, reduced natural resources, and difficulty in predicting climate, making food security a significant problem in several countries. Therefore, the technology trend of using the Internet of Things (IoT) with case studies in agriculture is a solution to increase the efficiency of the crop cultivation process and increase agricultural productivity. Currently, the use of IoT technology in the agricultural sector uses Wireless Sensor Network (WSN) technology and data analytics for data processing. This IoT platform combines several other technologies, such as WSN, cloud computing, middleware architecture, end-user application, and radio frequency identification (RFID). There are several benefits and challenges regarding the use of IoT technology for the agricultural sector. This paper will discuss the IoT platform and architecture and enable the application of the concept of smart agriculture. © 2020 IEEE.

关键词： Internet of things

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A smart glove of combining virtual and real environments for chemical experiment 2020

A smart glove of combining virtual and real environments for...

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6th international conference on computing and data Engineering, ICCDE 2020 and 2020 international conference on Artificial Intelligence in Electronics Engineering, AIEE 2020

作者： Meng, Xin Feng, Zhiquan Tian, Jinglan Department of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9781450376730

In the existing virtual experimental teaching platform, there is a lack of operation on real experimental equipment, and most of them only interact with users through a single mode. Users lack the real sense of experimental operation, and the virtual experimental platform cannot accurately capture users' intentions. In view of the above problems, this paper designs a smart glove based on IMU (inertial measurement unit), and proposes a multimode fusion intention perception algorithm based on vision, gesture and voice data. Finally, the smart glove is applied to the thick sulfuric acid dilution experiment platform which combines virtual and real environments. The experiment proves that the intelligent glove designed in this paper can accurately obtain the user's hand posture and operational intention. Under the unsupervised environment, the user can successfully complete the concentrated sulfuric acid dilution experiment by talking with the glove, and the nature of human-computer interaction is improved and get a good user evaluation. © 2020 ACM international conference Proceeding Series. All rights reserved.

关键词： Human computer interaction

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4th EAI international conference on Industrial IoT Technologies and Applications, Industrial IoT 2020

4th EAI International Conference on Industrial IoT Technolog...

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4th EAI international conference on Industrial IoT Technologies and Applications, Industrial IoT 2020

ISBN: (纸本)9783030710606

The proceedings contain 14 papers. The special focus in this conference is on Industrial IoT Technologies and Applications. The topics include: Power-Based Intrusion Detection for Additive Manufacturing: A Deep Learning Approach;a Proposal for Monitoring Grass Coverage in Citrus Crops Applying Time Series Analysis in Sentinel-2 Bands;Correlation of NDVI with RGB data to Evaluate the Effects of Solar Exposure on Different Combinations of Ornamental Grass Used in Lawns;deployment and Assessment of a LoRa Sensor Network in Camelina [Camelina sativa (L.) Crantz] Culture;real-Time Task Scheduling in smart Factories Employing Fog computing;an Efficient Network-Wide Reliable Broadcast Protocol for Medical Sensor Networks;beyond Anchors: Optimal Equality Constraints in Cooperative Localization;End-to-End Error Control Coding Capability of NB-IoT Transmissions in a GEO Satellite System with Time-Packed Optical Feeder Link;decentralized Brains: A Reference Implementation with Performance Evaluation;wireless Sensor Network to Create a Water Quality Observatory in Coastal Areas;an intelligent Predictive Maintenance Approach Based on End-of-Line Test Logfiles in the Automotive Industry;towards Construction Progress Estimation Based on Images Captured on Site.

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smart Agriculture as a Cyber Physical System: A Real-World Deployment 4

Smart Agriculture as a Cyber Physical System: A Real-World D...

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4th international conference on intelligent computing in data Sciences (ICDS)

作者： Et-taibi, Bouali Abid, Mohamed Riduan Boumhidi, Ismail Benhaddou, Driss Sidi Mohammed Ben Abdellah Univ Fac Sci Fes Morocco Al Akhawayn Univ Sch Sci & Engn Ifrane Morocco Univ Houston Sch Sci & Technol Houston TX USA

ISBN: (纸本)9781728180847

Water is becoming a scarce resource. With the steadily increasing demand on food, the optimization of resources usage proves indispensable for a sustained agriculture. In this context, smart Agriculture (SA) is emerging as a promising field leveraging on the introduction of ICT (Information & Communication Technology) with the ultimate goal of both optimal usage of resources (e.g., groundwater, fertilizers, and electrical energy) and better crop yields. The smartness of SA stems from the real-time data acquisition, processing, and dissemination. SA is a Cyber Physical System (CPS). It continuously monitors and acts upon physical entities (e.g., soil, weather, pumps, etc.). Wireless sensors/actuators, along with the control unit, constitute, the main ICT components in SA. In this paper, we shed further light onto the ICT components of SA and present the details of a real-world testbed deployment. We present the system architecture, the wireless communication infrastructure, and the processing behind the control unit. The latter is an intelligent system using Fuzzy logic. Furthermore, we present venues for renewable energy integration into SA and advocate the use of batteries for optimal energy usage.

关键词： smart Agriculture Wireless Sensors Fuzzy Control

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A Robust Image Security System for Cloud-Based smart Campus Using LBP and PCA 3rd

A Robust Image Security System for Cloud-Based Smart Campus ...

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3rd international conference on Communications and Cyber Physical Engineering, ICCCE 2020

作者： Mannan, Mohd Ahmed Abdul Gupta, Gulabchand K. Department of Computer Engineering JJT University JhunjhunuRajasthan India Seva Sadan College of Arts Science & Commerce Ulhasnagar ThaneMaharashtra India

ISBN: (纸本)9789811579608

Most of the educational institutes now days because of increased threat to the campus security have started installing the biometric security support system for personal identification. In real time situation, a large number of biometric data get accumulated which could be an unbearable burden for the biometric security system of a digital smart campus. This had attracted the research community in the field of computer vision and security to use the convenience of cloud computing and store their large data set to cloud servers. During the transform of the bulky data to the cloud source there is necessity of reducing the computational burden and storage burden on the intelligent biometric security system. In this paper a enhanced method for personal identification using biometric system in cloud environment is proposed in which first biometric images are encrypted using either block encryption technique or pixel encryption technique. Out of these encrypted images local binary pattern (LBP) features are extracted for identification or classifications due to which privacy can be preserved. Further PCA is applied on LBP which helps to reduce the computational time and data transfer time to cloud. These extracted features using LBP and PCA are used for equivalent image retrieval using histogram equalization technique for personal identification. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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A study of teaching model construction under big data background-taking 《computer information technology》 for example

A study of teaching model construction under big data backgr...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Zheng, Jun Network Information Center Baotou Teachers’ College Baotou China

ISBN: (纸本)9789811525674

The advent of the era of big data has driven rapid development of the educational industry, and meanwhile proposed higher requirements for informatization of education and teaching. As for modern education, the concept of big data must be introduced into the daily education and teaching. Teaching objectives, teaching model, and pre-class, in-class and after-class teaching activity models under the big data background were designed in this paper, and a teaching case was designed by taking the Computer Information Technology course for example. Teaching data were collected through the big data teaching platform, followed by an intelligent analysis. In the end, the new-type teaching model was constructed and implemented under the big data background. This teaching model has exerted a promoting effect on educational informatization and provided a big data-based classroom teaching model which can be used for reference. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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Object Recognition: Distributed Architecture Based on Heterogeneous Devices to Integrate Sensor Information 16th

Object Recognition: Distributed Architecture Based on Hetero...

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16th international Symposium on Distributed computing and Artificial Intelligence (DCAI)

作者： Poza-Lujan, Jose-Luis Posadas-Yague, Juan-Luis Munera, Eduardo Simo, Jose E. Blanes, Francisco Univ Politecn Valencia Univ Inst Control Syst & Ind Comp Ai2 Camino Vera S-N E-46022 Valencia Spain

ISBN: (纸本)9783030238872;9783030238865

Object recognition is a necessary task for many areas of technology, such as robot navigation or the intelligent reconstruction of environments in order a robot can interact with these objects. This article presents an architecture that integrates distributed heterogeneous information to recognise objects. The architecture uses devices that can process sensory data locally to send information to other devices. In order to perform data processing actions, the devices must have a layer of intelligent connectivity. These devices are called smart Resources that offer to the distributed nodes the processed sensor data by means of information services. To validate the architecture, a system with two smart resources, equipped with different sensors, has been implemented. Experiments carried out show that it is better to select objects as soon as possible to improve the object recognition rate. Consequently, in the distributed system, devices should, when possible, deliver the process in advance.

关键词： smart environment Distributed systems Distributed architectures Object detection Information integration

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Deep Reinforcement Learning for the management of Software-Defined Networks in smart Farming

Deep Reinforcement Learning for the management of Software-D...

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2nd IEEE international conference on Omni-Iayer intelligent Systems (IEEE COINS)

作者： Alonso, Ricardo S. Sitton-Candanedo, Ines Casado-Vara, Roberto Prieto, Javier Corchado, Juan M. Univ Salamanca BISITE Res Grp Salamanca Spain AIR Inst IoT Digital Innovat Hub Salamanca Spain

ISBN: (纸本)9781728163710

The Internet of Things and the millions of devices that generate and collect data through sensors to send it to the Cloud are part of the life of users in many contexts, including smart farming and precision agriculture scenarios. This volume of data is stored and processed in the Cloud, with the purpose of obtaining knowledge and valuable information for organizations. Edge computing has emerged to reduce the costs associated with transferring, processing and storing data from IoT environments in the Cloud. This paradigm allows data to be pre-processed at the edge of the network before they are sent to the Cloud, obtaining shorter response times and maintaining service even during communication breakdowns between the IoT and Cloud layers. Furthermore, there is a increasing trend to shared physical network resources among diverse user entities through Software-Defined Networks and Network Function Virtualization with the aim to reduce costs. In this sense, smart mechanisms are required to optimize virtual dataflows in the networks, as Deep Reinforcement Learning techniques. This paper proposes a Double Deep-Q Learning approach to manage virtual dataflows in SDN/NFV using an Edge-IoT architecture, formerly applied in smart farming and Industry 4.0 scenarios.

关键词： Internet of Things Software Defined Networks Reinforcement Learning Network Function Virtualization smart Farming

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New Algorithm of QoS Constrained Routing for Node Energy Optimization of Edge computing 17

New Algorithm of QoS Constrained Routing for Node Energy Opt...

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17th IEEE international conference on Mobile Ad Hoc and smart Systems (IEEE MASS)

作者： Zhang, Degan Du, Jinyu Zhang, Ting Yang, Peng Fan, Hongrui Tianjin Univ Technol Tianjin Key Lab Intelligent Comp & Novel Software Tianjin 300384 Peoples R China Tianjin Univ Technol Key Lab Comp Vis & Syst Minist Educ Tianjin 300384 Peoples R China

ISBN: (纸本)9781728198668

We propose an oriented edge computing nodes energy optimized QoS constrained routing algorithm. The mechanism of this algorithm is to optimize the network energy consumption and extend the network life cycle by creatively combining the edge computing technology to preprocess the original data of the node, accelerating the transmission and processing of effective data, accelerating the algorithm convergence by using the way of automata interacting with the environment and controlling the dormant activation state of the node. Through experimental testing and comparison, this paper gave the Multi-QoS constrained routing algorithm for Edge computing and Node energy optimization algorithm (MQEN), which can meet the requirements of end-to-end delay and reliability service with multi-QoS constraints when significantly reducing network energy consumption.

关键词： Qos wireless sensor edge computing learning automata machine learning energy-aware

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Student-Facing Educational Dashboard Design for Online Learners 18

Student-Facing Educational Dashboard Design for Online Learn...

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18th IEEE international conference on Pervasive intelligent and computing (PICom)

作者： Farahmand, Arta Dewan, M. Ali Akber Lin, Fuhua Athabasca Univ Fac Sci & Technol Sch Comp & Informat Syst Athabasca AB Canada

ISBN: (纸本)9781728166094

The current shift from traditional classrooms to online learning in higher education calls for more attention to selfregulated learning. This research is motivated by the growing interest in potential of using learning analytics dashboard (LAD) to increase individuals' self-regulation by creating visibility into their performance in various applications. This study explores how data visualization can be integrated with online learning to improve learners' performance through enhancing their skills in planning and organization. We are working on the design of a comprehensive LAD, focusing on micro-level of learning analytics to support learning activities of students. The LAD includes the following two features to enhance students' self-regulation in online learning: (1) a function to track students' progress compared to other students' over time;(2) reminders to help students with upcoming deadlines and auto-generating to do lists. The hypothesis is that the LAD will increase students' engagement, motivation, and self-regulation in an online learning environment. This study is significant because it contributes to the body of knowledge by exploring how student-generated data can be used to improve selfregulated learning. The practical contribution of this study is to create a personalized LAD for students based on the learnergenerated data to benefit students' organization skill, planning skill, and motivation.

关键词： learning analytics dashboard online learning learning management system information visualization data mining self-regulated learning

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