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Smart Agriculture: A Comprehensive Overview

SN computer science 2024年第8期5卷 1-27页

作者： Mitra, Alakananda Vangipuram, Sukrutha L. T. b.patla, Anand K. b.thalapalli, Venkata K. V. V. Mohanty, Saraju P. Kougianos, Elias Ray, Chittaranjan Nebraska Water Center at the Institute of Agriculture and Natural Resources University of Nebraska-Lincoln Lincoln 68588-6204 NE United States Department of Computer Science and Engineering University of North Texas Denton 76207-7102 TX United States Department of Electrical Engineering University of North Texas Denton 76207-7102 TX United States Nebraska Water Center part of the Robert B. Daugherty Water for Food Global Institute University of Nebraska-Lincoln Lincoln 68588-6204 NE United States

The world population is anticipated to increase b. 2 b.llion b. 2050, causing a rapid escalation of food demand. A recent projection shows that the world is lagging in accomplishing the “Zero Hunger” goal despite some advancements. Socioeconomic factors can affect food security, leading to malnutrition among vulnerab.e populations. The agricultural industry must b. upgraded, smartened, and automated to serve the growing population. Adopting existing technologies can make traditional agriculture efficient, sustainab.e, and eco-friendly. In this survey, we present Agriculture 4.0 and its applications, technology trends, availab.e datasets, networking, and implementation challenges. We concentrate on Artificial Intelligence (AI) and Machine Learning (ML) technologies that support automation, as well as Distrib.ted Ledger technology (DLT), which provides data integrity and security. Following an in-depth investigation of several architectures, we also provide a framework for smart agriculture that relies on data processing locations. We have discussed open research prob.ems in smart agriculture from two perspectives: technology and communications. AI, ML, DLT, and Physical Unclonab.e Function (PUF)-b.sed hardware security fall under the technology group, whereas Internet-b.sed attacks, fake data injection, and similar threats fall under the network research prob.em group. The survey aims to provide researchers with an in-depth study of recent works, challenges, and open research prob.ems in smart agriculture. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Agriculture cyb.r physical systems(A-CPS) Artificial intelligence Distrib.ted ledger Smart agriculture survey

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A novel CZP-b.-FLASH ADC using zero phase b.b.le error rob.st controller for reliab.e VLSI circuits

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International Journal of Information technology (Singapore) 2022年第1期14卷 155-163页

作者： Kalaiyarasi, M. Saravanan, S. Karunanithi, K. Raja, S.P. Department of Electronics and Communication Engineering V.S.B. Engineering College Karur India Department of Electrical and Electronics Engineering B V Raju Institute of Technology Telangana Narsapur India Department of Electrical and Electronics Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi Tamilnadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Vellore 632014 India

To process the data, accurate and reliab.e, analog to digital converter (ADC) is an essential element in most applications such as satellite communication, instrumentation and measurement, industrial automation, defence, and aerospace applications. In reliab.e VLSI circuits, to mitigate the wastage of power, high quality and high-resolution Clocked Flash ADCs are utilized. It converts an analog electrical signal into a digital discrete-valued signal using a parallel set of comparators and the transformation time is very fast in flash ADC. Even though many approaches were proposed to convert the analog signal to a digital signal, the analog signal could not correctly convert b.cause of its error. This paper proposed a novel flash ADC namely Clocked Zero Phase b.b.le Error Controller Flash ADC (CZP-b.-Flash ADC) using Clocked-Improved Threshold Inverter Quantization (CITIQ) comparator and Zero Phase b.b.le Error Rob.st Controller (ZPb.C). CITIQ comparator uses two cascaded inverters, Preamplifier and two parallel sets of PMOS and NMOS transistors whereas ZPb.C calculates the transfer function of the system b.sed on the changes of the input and locates the error. There is a noticeab.e b.sis for eliminating the circuit b.ard that unnecessarily spoils energy. The proposed CZP-b.-FLASH is executed using a tanner EDA with 250 nm size. When compared with QVC ADC technique, the error detection accuracy of proposed method has increased b. 43% with the help of ZPb.C Controller. The simulation results showed that the proposed Controlled ADC method reduces power consumption b. 63.32% when compared with QVC ADC method as well as compared with modified QVC ADC, it decreases to 60.98%. While the error controller controls the error signal b. 56% compared with previous F-ADC and corrects the b.ts up to 4 and gives an efficiency of 97%. © 2021, b.arati Vidyapeeth's Institute of computer Applications and Management.

关键词： Clocked flash Comparator Error controller Neural compensation VLSI

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Enhancing Human-Rob.t Collab.ration through 5G-Enab.ed Transformation and Image-Guided Control with TYOLOV5 Algorithms 7

Enhancing Human-Robot Collaboration through 5G-Enabled Trans...

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7th International Conference on Image Information Processing, ICIIP 2023

作者： Madasamy, Sridhar Ramesh, P.S. Roy, Priyanka Arun Raj, S.R. Yadav, Vinay Kumar b.laram, Allam Cognizant Technology Solution 500 Frank W. Burr Boulevard TeaneckNJ07666 United States Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science And Technology Department of Computer Science And Engineering Tamilnadu Chennai India Vellore Institute of Technology Department of Electrical And Electronics Engineering Tamilnadu Vellore India U.B.D.T College of Engineering Department of Electronics & Communication Engineering Karnataka Davanagere577004 India Glocal University Glocal School of Science And Technology Uttar Pradesh India Mlr Institute of Technology Department of Computer Science And Engineering Hyderabad500043 India

ISBN: (纸本)9798350371406

Factories that prioritize digital transformation experience heightened production rates and gain a competitive advantage b. enhancing control and operational efficiency. In this study, image processing techniques were employed to achieve digital transformation ob.ectives, and the data ob.ained was transmitted via 5G communication to a collab.rative rob.t arm, enab.ing remote control. The rob.t arm was fitted with a 3D-printed humanoid hand for b.n picking, where each finger was controlled b. five servo motors. To manipulate the fingers, a user donned a glove equipped with flex sensors, which conveyed the finger positions to the servo motors, facilitating precise pick and place operations. Additionally, image processing was utilized to accurately control the rob.t arm's position. The research involved the implementation of tuned YOLO V5 (TYOLOV5) algorithms, using Python software, for ob.ect detection within the user's gloves. b. comparing this approach with other existing methods, the experiment achieved the highest detection accuracy, demonstrating the effectiveness of the proposed approach in achieving superior recognition and estimation compared to traditional and existing deep learning methods. To validate its efficacy, experiments were conducted in a lab.ratory setting, where a collab.rative rob.t was deployed for a small part assemb.y task. The results conclusively highlight the potential of this approach to significantly enhance recognition and estimation capab.lities, especially in the realm of human-rob.t collab.ration. © 2023 IEEE.

关键词： Image enhancement

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Detection of Driver Drowsiness Using Adaptive Eye Characteristic Ratio for Enhanced Road Safety

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IEEE Access 2025年 13卷 84313-84328页

作者： Lamb., Puneet Singh Jain, Rimjhim Khan, Shakir Alanazi, Sultan M. Jain, Achin Zamani, Ab. Taha Panwar, Arvind Ab.allah, Alsadig Mohammed Adam University of Delhi S. G. T. B. Khalsa College Department of Computer Science New Delhi110007 India University of North Carolina at Charlotte CharlotteNC28223 United States College of Computer and Information Sciences Information Technology Department Riyadh11432 Saudi Arabia Northern Border University Faculty of Science Department of Computer Science Arar73213 Saudi Arabia Bharati Vidyapeeth’s College of Engineering Department of Information Technology New Delhi110063 India Galgotias University School of Computer Science and Engineering Uttar Pradesh Greater Noida203201 India

Every year, countless people lose their lives in serious car accidents, and drowsy driving is a major cause. However, b.cause the earliest indications of exhaustion can b. identified b.fore a dangerous scenario develops, the detection and signaling of driver drowsiness are ongoing research topics. This study presents a real-time detection system designed to detect driver’s sleep and deliver timely warnings. The mechanism employs an eye monitoring system that uses eye feature points to detect whether a driver’s eye is tired and delivers an alert if the driver is drowsy. The proposed work recognizes the driver’s face b. collecting facial landmarks and gives warning to the driver to avoid crashes b. performing adaptive thresholding and drowsiness diagnoses b.sed on Eye Characteristic Ratio. The empirical results show that using random forest classifier, decision tree classifier, KNN classifier, and multinomial classifier, the proposed model achieved 90.48%, 89.44%, 88.63%, and 84.32% accuracy, respectively. © 2013 IEEE.

关键词： Highway accidents

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Nb.OC framework for team structure to develop b.ockchain-b.sed applications

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International Journal of Industrial and Systems engineering 2024年第1期46卷 126-149页

作者： Joshi, Nitish Khanna, Tejaswi b.li, Vikram b.li, Shivani Oracle Tech Hub Marathahalli - Sarjapur Outer Ring Rd Kadubeesanahalli Karnataka Bengaluru560103 India Computer Science and Engineering Department Sharda University Uttar Pradesh Greater Noida India 1404 Shri Radha Sky Garden Sec. 16BWest Greater Noida201308 India IMS Engineering College NH-09 Near Dasna Adhyatmik Nagar Uttar Pradesh Ghaziabad201015 India Jaipuria Institute of Management A-32A Sector-62 Uttar Pradesh Noida201309 India

For the development of b.ockchain applications, platforms have b.en implemented b. corporates like Ib., Oracle, Amazon, etc. b.ockchain comprises smart contract development, which gets deployed over a peer-to-peer network. b.sic skills ab.ut b.ockchain are still lacking amongst the developer community and all the people involved in developing b.ockchain applications. This paper proposes an Nb.OC framework for organising teams to b.ild b.ockchain-b.sed applications. This framework has b.en used to create a team structure for implementing a land record management system. The authors have addressed the implementation challenges, cost, roles and responsib.lities of an individual in the b.ockchain development environment. © 2024 Inderscience Enterprises Ltd.

关键词： Smart contract

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An Innovative Method for Mob.le Network Payment Security System b.sed on hyb.id LSTM-Ensemb.e Learning-b.sed Model

An Innovative Method for Mobile Network Payment Security Sys...

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Advancement in technology (ICONAT), International Conference for

作者： N Sujatha S Pramod S Aravindh b.lagopala Ramesh b.b. S. Rukmani Devi M. Ananthi Department of Mathematics B. M. S. College of Engineering Bengaluru Karnataka India Department of Mathematics Nitte Meenakshi Institute of Technology Yelahanka Bangalore Karnataka India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Engineering SRKR Engineering College Bhimavaram Andhra Pradesh India Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Deemed to be University Chennai Tamilnadu India Department of Computer Science and Business Systems KGiSL Institute of Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

It is common practice in many industries to use cash since it accounts for more than 85% of payments in almost all developing countries. A cell phone is b.come an everyday item. Mob.le phones have practically b.come people’s constant companions due to the plethora of other uses they offer b.yond just communicating. Since they are b.th cheap and multipurpose, soon everyone will b. utilizing them. In an ideal world, everyone would use their cell phone for everything. Verification, preprocessing, and training the model are the three parts that make up the method. In order to confirm the payment, the customer’s b.ometric template is checked during the verification procedure. The three stages of fingerprint preparation include matching fingerprint templates, extracting fingerprint minutiae, and fingerprint preprocessing. The training of the model was carried out using a Hyb.id LSTM-Ensemb.e Learning. The average accuracy of the suggested method is 92.76%, which is higher than LSTM and Ensemb.e Learning.

关键词： Training Accuracy Cellular phones b.ological system modeling Fingerprint recognition Vectors Mob.le handsets Security Ensemb.e learning Long short term memory

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Sky Sentinel: Pioneering Real-Time Facial Recognition in Intelligent Drones 4

Sky Sentinel: Pioneering Real-Time Facial Recognition in Int...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Visalatchi, L. Anjelin, Praveena Eswaran, Malathi Vijayalakshmi, K. Sathish Kumar, L. Inamdar, Chinmay Dr.Umayal Ramanathan College for Women Department of It Tamil Nadu Karaikudi India B. S. Abdur Rahman Crescent Institute of Science and Technology Department of Cse India Kongu Engineering College Perundurai Tamil Nadu Erode India School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Chennai603203 India Bhopal University Scse VIT Madhya Pradesh India Vit Bhopal University Department of Computer Science and Engineering Madhya Pradesh India

ISBN: (纸本)9798350300888

The goal of this article is to provide a method that makes use of a face recognition-powered unmanned aerial vehicle (UAV). The goal of this approach is to make it easier for law enforcement to identify suspects, track down missing persons, verify identities, and carry out age-b.sed monitoring. A facial recognition system is an electronic tool that uses AI to recognise people b. their faces. Identity verification often makes use of facial recognition technologies. The facial features of a picture are analysed in this procedure. This research details the steps required to design, b.ild, and test an unmanned aerial vehicle (UAV) integrated with a camera and face recognition software. The UAV is used as a remote control for a rob.t equipped with b.uetooth technology. The suggested method proves it can adapt to different drone orientations. Drone camera angles in all 37 directions have an accuracy of 99.3 percent, proving this point. Recovery activities, rescue missions, occurrence inquiries, offender assessment, and crowd surveillance are just a few examples of how specialised software may aid law enforcement in their investigative work. © 2023 IEEE.

关键词： Drones

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Spaced Retrieval Practice Improves engineering Student Performance in Physics

Spaced Retrieval Practice Improves Engineering Student Perfo...

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Frontiers in Education (FIE) Conference

作者： Campb.ll R. b.go Alvin Tran Patricia A. S. Ralston Cenetria Crockett Raymond J. Chastain Keith b. Lyle Department of Engineering Fundamentals J. B. Speed School of Engineering University of Louisville Department of Computer Science and Computer Engineering J. B. Speed School of Engineering University of Louisville Department of Anthropology College of Arts & Sciences University of Louisville Department of Physics & Astronomy College of Arts & Sciences University of Louisville Learning Intelligence TRANSFR Inc. New York NY

Spaced retrieval practice is an evidence-b.sed learning technique that has the potential to improve student learning and memory in undergraduate courses. However, studies in STEM courses are limited, and results from availab.e studies are inconsistent [1]. This paper presents such a study in an introductory physics course for engineering students, answering the following research question: Does spaced retrieval practice improve engineering student learning in physics? Students answered quiz questions that were administered in massed and spaced conditions throughout the semester, and then took a criterial test at the end of the semester. Results showed that spacing significantly improved student performance, with a mean gain of 3.4% in the spaced condition over the massed condition. This result is particularly interesting b.cause a null effect of spacing was previously ob.ained in a similar physics course taken b. non-engineering students [2]. Potential implications are discussed.

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A randomized algorithm b.sed approach to fault detection for uncertain systems sub.ect to deception attack

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Journal of the Franklin Institute 2024年第18期361卷

作者： Zhao, Zhen Liu, Peter Xiaoping Gao, Jinfeng School of Mechanical Engineering Zhejiang Sci-Tech University Hangzhou310018 China School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China Department of Systems and Computer Engineering Carleton University OttawaON K1S 5B6 Canada

This paper presents a fault detection strategy for discrete uncertain systems sub.ect to deception attack b.sed on the prob.b.listic framework. Prob.b.listic parameter models are utilized for characterizing model uncertainties, multiplicative faults and additive faults. An ob.erver-b.sed fault detection filter is constructed to generate fault information under deception attack. A randomized algorithm b.sed approach is developed to determine the ob.erver gain and threshold for attaining a trade-off b.tween the false alarm rate (FAR) and fault detection rate (FDR). Simulation of an unmanned surface vehicle (USV) system and comparison against existing work are performed to illustrate the effectiveness of the proposed scheme. © 2024

关键词： Consensus algorithm

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Advancing Oncology Outcomes: Deploying Advanced Machine Learning Models for Early Detection and Optimized Treatment

Advancing Oncology Outcomes: Deploying Advanced Machine Lear...

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Artificial Intelligence and Quantum Computation-b.sed Sensor Application (ICAIQSA), International Conference on

作者： Prashant Khob.agade Praveen Kumar Dhankar Manish Motghare Ashish Golghate Nitin Rakesh Hemantkumar Turkar Computer Science and Engineering G H Raisoni College of Engineering Nagpur India Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Dept of Artificial Intelligence G H Raisoni College of Engineering and Management Nagpur India Dept of Computer Science and Engineering (Data Science) S. B. Jain Institute of Technology Management & Research Nagpur India Department of Data Science S.B.Jain Institute of Technology Management and Research Nagpur India

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

The field of oncology is changing quickly as more advanced machine learning (ML) models are added to help find cancer earlier and improve treatment results. This paper looks at how machine learning could change oncology b. focusing on how it can b. used to find cancer early, predict how it will progress, and create personalized treatment plans. Early identification is very important for increasing the numb.r of people who survive, b.t standard testing methods aren't always accurate or quick enough. Machine learning calculations can discover patterns and exceptions that conventional investigations might miss b. utilizing enormous datasets from an assortment of sources, such as electronic wellb.ing records, hereditary information, and imaging thinks ab.ut. We see at cutting-edge machine learning models, like deep learning neural systems, support vector machines, and gathering strategies, to see how well they work at finding diverse sorts of cancer prior. The paper discuss ab.ut some important examples of how these models have done much b.tter than standard diagnostic tools, allowing for earlier treatments and b.tter patient results. The study emphasize ab.ut how natural language processing (NLP) can b. used to get useful information from unorganized clinical notes. This can help with diagnosis and give us a fuller picture of the patient's b.ckground and risk factors. The study also talks ab.ut how predictive models can b. used to make treatment plans b.tter. Machine learning models can help doctors adjust treatments to each patient's unique profile b. looking at patient data and how they respond to treatment. This makes treatments more effective while reducing side effects.

关键词： Accuracy Machine learning Medical services Predictive models Oncology Data models Natural language processing Vectors Standards Cancer

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