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Smart and Quick Parking Spot Detection

Smart and Quick Parking Spot Detection

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International conference on Computing and Networking Technology (ICCNT)

作者： Santhosh Kumar Veeramalla Rama Lakshmi Gali M Ranjeeth Saikumar Tara V Hindumathi L Bhargava Kumar Department of ECE BVRIT HYDERABAD College of Engineering for Women Hyderabad India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The rapid expansion of urban areas has intensified the challenge of finding parking spaces for drivers. Intelligent parking systems emerge as a crucial solution by providing real-time detection of available spaces. While various methods exist, from basic magnetic sensors to advanced computer vision algorithms, their effectiveness can be hindered by environmental factors. Recognizing the importance of automated systems, this paper focuses on implementing an image processing approach for parking space detection. By strategically placing cameras in parking lots, the system identifies vacant spaces and transforms images to determine availability. Integrating these techniques into mobile applications could further aid drivers in locating parking spots, improving their overall experience. Ultimately, accurate and efficient parking space identification is vital for reducing congestion, enhancing air quality, and improving urban environments.

关键词： Wireless sensor networks Transmitters Urban areas Transforms Streaming media Cameras User experience Real-time systems Automobiles Vehicles

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Crop Detection and Weed Removal Agriculture Robot

Crop Detection and Weed Removal Agriculture Robot

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Intelligent systems and advanced applications (ICISAA), International conference on

作者： Digambar P. Patil Digvijay B. Kanase Seema S. Patil Deepak B. Patil Himmat Singh Purohit Nupoor Mhatre Department of Automation and Robotics Dr. D. Y. Patil Institute of Technology Pune Maharashtra India Department of Electrical Engineering Dr. D. Y. Patil Institute of Technology Pune Maharashtra India Department of E&Tc Engineering Ashokrao Mane Group of Institutions Kolhapur Maharashtra India Electronics and Telecommunication Engineering Department NMIET Talegaon Dabhade Pune Maharashtra India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

Weed management is important thing of modern agriculture, as weeds can significantly impact crop yields, increase production costs, and pose environmental challenges. Weeds are unwanted plants that make race with desirable crops for resources such as nutrients, sunlight and water. It can cause significant damage to crops and other vegetation if left uncontrolled. The use of herbicides to control weeds can result in environmental pollution if not applied properly or if excessive amounts are used. Continuous use of herbicides without proper rotation or alternative weed management strategies can lead to the development of herbicide-resistant weed populations. Weed presence in harvested crops can reduce their quality, making them less marketable. The weed removal robot will be equipped with various sensors to scan the field and detect the presence of weeds. advanced computer vision algorithms and machine learning techniques are often employed to differentiate between crops and weeds based on color, shape, or other characteristics. sensors scan the field and capture images or data that are then processed by the processor. The single board computer can be programmed to recognize the visual differences between crops and weeds based on color, shape, or other characteristics. This robot will be equipped with precise actuators, which can include mechanical arms or electric tools. These actuators are used to perform the actual weed removal tasks. The processor controls the weed removal mechanism, which could be a mechanical arm with tools like rotating brushes or blades for physical weed removal

关键词： YOLO Actuators Shape Image color analysis Crops sensor phenomena and characterization Robot sensing systems Manipulators Agriculture Farming

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Electronic Prognostics Innovations for applications to Aerospace systems

Electronic Prognostics Innovations for Applications to Aeros...

引用

IEEE conference on Aerospace

作者： Matthew Gerdes Kenny Gross Guang Chao Wang Oracle Corporation

Oracle has an anomaly detection solution for monitoring time-series telemetry signals for dense-sensor IoT prognostic applications. It integrates an advanced prognostic pattern recognition technique called Multivariate State Estimation Technique (MSET) for high-sensitivity prognostic fault monitoring applications in commercial nuclear power and aerospace applications. MSET has since been spun off and met with commercial success for prognostic Machine Learning (ML) applications in a broad range of safety critical applications, including NASA space shuttles, oil-and-gas asset prognostics, and commercial aviation streaming prognostics. MSET proves to possess significant advantages over conventional ML solutions including neural networks, autoassociative kernel regression, and support vector machines. The main advantages include earlier warning of incipient anomalies in complex time-series signatures, and much lower overhead compute cost due to the deterministic mathematical structure of MSET. Both are crucial for dense-sensor avionic IoT prognostics. In addition, Oracle has developed an extensive portfolio of data preprocessing innovations around MSET to solve the common big-data challenges that cause conventional ML algorithms to perform poorly regarding prognostic accuracy (i.e. false/missed alarm probabilities). Oracle's MSET-based prognostic solution helps increase avionic reliability margins and system availability objectives while reducing costly sources of “no fault found” events that have become a significant sparing-logistics issue for many industries including aerospace and avionics. Moreover, by utilizing and correlating information from all on-board telemetry sensors (e.g., distributed pressure, voltage, temperature, current, airflow and hydraulic flow), MSET is able to provide the best possible prediction of failure precursors and onset of small degradation for the electronic components used on aircrafts, benefiting the aviation Prognostics and Health Mana

关键词： Temperature sensors Degradation Technological innovation Aerospace electronics sensor systems sensors Telemetry

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Research on Task Scheduling Methods for Intelligent Connected Vehicles with End-to-End Delay Constraints

Research on Task Scheduling Methods for Intelligent Connecte...

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IEEE International conference on Industrial Informatics (INDIN)

作者： Shichun Yang Wenlong Chen Boao Zhang Qianlong Duan Bide Hao Xiaoyu Yan School of Transportation Science and Engineering Bei Hang University Beijing China Research Institute of Aero-Engine Bei Hang University Beijing China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

With the rapidly growing Intelligent Connect-ed Vehicle (ICV) industry, modern advanced Driver Assistance systems (ADAS) integrate critical and non-critical software functions on the same hardware platform. These functions have complex timing requirements and associated dependencies. To ensure the real-time safety of critical au-tomotive applications, complex task chains with dependencies generated by automotive applications (e.g. sensor data acquisition, data processing, and control execution) must meet the worst end-to-end latency. The resulting task sched-uling problem requires the assignment of tasks to available cores for execution and the generation of static schedules that satisfy the timing constraints of the tasks and the end-to-end latency of the task chain. In this paper, a task sched-uling and task mapping method based on an intelligent heu-ristic algorithm is proposed for the ADAS platform, and simulated scheduling based on the EDF algorithm. The op-timal task scheduling scheme is selected by calculating the fitness function by the intelligent heuristic algorithm, and the simulated annealing algorithm (SA) is selected as the benchmark for the experiment. The experimental results show that the grey wolf optimizer converges faster and finds a better scheduling scheme, which reduces the total time of scheduling tasks.

关键词： Schedules Job shop scheduling Processor scheduling Heuristic algorithms Optimal scheduling Transforms Simulated annealing Software Delays advanced driver assistance systems

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Fuzzy Logic Framework for Internet of Things systems Implementation 15

Fuzzy Logic Framework for Internet of Things Systems Impleme...

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15th International conference on advanced Technologies, systems and Services in Telecommunications, TELSIKS 2021

作者： Zoican, Sorin Zoican, Roxana Galatchi, Dan Politehnica University of Bucharest Faculty of Electronics Telecommunications and Information Technology Splaiul Independentei 313 Bucharest060042 Romania

ISBN: (纸本)9781665444422

This paper presents a framework to implement an Internet of Things (IoT) system using fuzzy logic. This framework provides general fuzzy membership functions that can be particularized for various applications implementing specific fuzzy rules to determine the system output. The motivation of this work is to create and test a flexible framework for the rapid implementation of IoT applications. Generic functions are implemented that are integrated into a commercial hardware platform. The framework is evaluated in terms of computation time and power consumption using a wireless sensor network (WSN) evaluation kit from Analog Devices. Also, a system for determining a person's health condition is illustrated as an application implementation example using the proposed fuzzy IoT framework. © 2021 IEEE.

关键词： Electric power utilization

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Enhanced Clustering Framework for Unveiling Hidden Patterns in IoT-Based Structured and Unstructured Data

Enhanced Clustering Framework for Unveiling Hidden Patterns ...

引用

International Symposium on advanced Computing and Communication (ISACC)

作者： Prabhat Das Karthik Kovuri Sajal Saha Department of IT The Assam Kaziranga University Department of CSE Adamas University Department of CSE The Assam Kaziranga University

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Clustering algorithms play a pivotal role in uncovering hidden patterns and relationships within diverse datasets. This study discusses about an enhanced real-time clustering approach based on the Birch methodology, optimized for analyzing both structured and unstructured data. Structured data, consisting of IoT sensor readings, and unstructured image data, captured using Raspberry Pi devices deployed in various locations, were analyzed to identify meaningful patterns. For structured data, the algorithm effectively clustered environmental parameters, revealing correlations and anomalies. For unstructured data, high-dimensional image features extracted using a pre-trained VGG16 model were clustered, uncovering patterns in texture, color, and structure. Experimental results demonstrate the algorithm’s scalability and efficiency, achieving high-quality clusters with average Silhouette Scores of 0.87 and 0.81 for structured and unstructured datasets, respectively. These findings highlight the algorithm’s adaptability and its potential for real-time analytics in diverse applications such as environmental monitoring and image-based decision-making systems.

关键词： Visualization Temperature distribution Correlation Image color analysis Scalability Clustering algorithms Feature extraction Real-time systems Environmental monitoring Object recognition

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Enhancing Mobility and Safety for Vulnerable Populations: An IoT-Enabled Smart Walking Frame with Mobile Application Integration

Enhancing Mobility and Safety for Vulnerable Populations: An...

引用

International conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)

作者： Ying Mei Leong Yau Kit Chung Lip Khi Lim Faculty of Computing and Engineering Quest International University Ipoh Malaysia School of Computing Newcastle University Newcastle United Kingdom

ISBN: (数字)9798331533137

ISBN: (纸本)9798331533144

The Smart Walking Frame revolutionizes mobility assistance for amputees and elderly individuals by seamlessly integrating Internet of Things (IoT) technology with a conventional walking frame. This innovative device addresses critical challenges in safety, independence, and emergency response for mobility-impaired users. The Smart Walking Frame incorporates an Arduino Uno microcontroller and a dedicated mobile application, offering advanced functionalities through embedded buttons. These include an alarm system for immediate attention, an SOS feature for emergencies, and sophisticated obstacle and water detection capabilities. By tackling issues such as limited situational awareness, difficulty in summoning immediate help, and lack of real-time location tracking, the device significantly enhances user mobility and security. Key innovations include the integration of multiple sensors for comprehensive environmental awareness, a Bluetooth-enabled mobile application for seamless control and monitoring, and a real-time GPS tracking system with SOS alerts. The accompanying mobile application extends the device's utility by enabling location tracking and allowing users to configure multiple emergency contacts. By combining these advanced features with the familiar form factor of a walking frame, the Smart Walking Frame offers a comprehensive solution to improve the quality of life and safety of individuals with limited mobility or self-defense capabilities, promising greater independence and peace of mind for users and their caregivers.

关键词： Legged locomotion Technological innovation Navigation sensor systems and applications Real-time systems Safety Mobile applications Internet of Things Older adults Monitoring

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Wireless Sensing for Simultaneous Human Vocal Sound and Heart Sound Recognition

Wireless Sensing for Simultaneous Human Vocal Sound and Hear...

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International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yu Rong Kumar Vijay Mishra Daniel W. Bliss Center for Wireless Information Systems and Computational Architectures (WISCA) Arizona State University Tempe AZ USA United States Army Research Laboratory Adelphi MD USA

Remote vibrometry using wireless signals is a recently introduced novel technique with a wide range of applications such as remote microphones and structural health monitoring. These use cases require high sensitivity and coherence in the sensing system. In this context, radar is a suitable all-weather sensor compared to conventional acoustic acquisition. We investigate human vocal sound and heart sound detection and separation using a single millimeter-wave radar sensor and advanced array processing techniques to achieve superior motion sensitivity.

关键词： Heart Wireless communication Wireless sensor networks Sensitivity Speech recognition Signal processing Acoustics

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Transforming Obesity Care Through Artificial Intelligence: Real-Case Implementations and Personalized Solutions

Transforming Obesity Care Through Artificial Intelligence: R...

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Computational Intelligence Approaches and applications (ICCIAA), International conference on

作者： Mayyas Al-Remawi Rami A. Abdel-Rahem Faisal Al-Akayleh Faisal Aburub Ahmed S.A. Ali Agha Department of Pharmaceutics and Pharmaceutical Technology University of Petra Amman Jordan Department of Chemistry Faculty of Arts and Sciences University of Petra Amman Jordan Faculty of Administrative & Financial Sciences University of Petra Amman Jordan Department of Pharmaceutical Sciences The University of Jordan Amman Jordan

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Obesity is a multifactorial condition that significantly increases the risk of metabolic syndrome, cardiovascular disease, and various other comorbidities. Conventional obesity management strategies-encompassing body mass index (BMI) measurements, dietary counseling, and caloric tracking-often fail to account for the heterogeneity of individual genetic, behavioral, and metabolic factors. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has emerged as a transformative approach, offering data-driven, personalized solutions that integrate electronic health records (EHRs), wearable sensor data, and multi-omics information. This article examines contemporary AI applications for obesity care, highlighting real-case implementations, technical and ethical considerations, and the future potential for optimizing patient outcomes. By leveraging advanced analytics, healthcare providers can enhance diagnostic precision, tailor interventions to individualized needs, and support sustained weight control, thus redefining the paradigm of obesity management.

关键词： Deep learning Obesity Ethics Weight control Force measurement Imaging Medical services Genetics Real-time systems Wearable sensors

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Detecting End Effector Command Pose Error Using Perfect Bit Field Imaging

Detecting End Effector Command Pose Error Using Perfect Bit ...

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International Carpathian Control conference (ICCC)

作者： Tomáš Buchta Jaroslav Hlava Tomáš Martinec Jaroslav Buchta Yegor Boyarchikov Department of Mechatronic Systems and Robotics Technical University of Liberec Liberec Czechia Institute of Mechatronics and Computer Engineering Technical University of Liberec Liberec Czechia

ISBN: (数字)9798331501273

ISBN: (纸本)9798331501280

This paper presents a novel approach to improving the precision of robotic arm operations in complex environments by using Perfect Bit Field Imaging (PBFI) for end effector command pose error detection. Accurate pose determination is essential for tasks such as manipulation, assembly, and autonomous navigation, particularly in space or hazardous settings where precision is critical. PBFI leverages high-resolution industrial cameras to capture detailed pixel-level information that can be used to correct the end effector’s position. The system’s key advantage is its low-cost nature, making it an attractive alternative to expensive sensor-based approaches. advanced image processing techniques are used to interpret bit fields, allowing for quick and reliable pose corrections that reduce the need for recalibration and minimize the impact of external disturbances. Additionally, the approach is adaptable to various robotic arm configurations and operational conditions, making it suitable for a wide range of industrial and space-based applications. This research opens new avenues for enhancing robotic precision in challenging environments, contributing to the advancement of cost-effective autonomous systems.

关键词： Accuracy Service robots Image processing Robot vision systems Refining End effectors Real-time systems Error correction Robots Optimization

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