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检索条件"任意字段=International Conference on Sensor Technologies and Applications, SensorComm"

共 9453 条记录，以下是1451-1460 订阅

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Review of Dynamic Spectrum Sharing: Techniques and Challenges

Review of Dynamic Spectrum Sharing: Techniques and Challenge...

引用

international conference on Optimization and applications (ICOA)

作者： Chaymaa Lakouismi Hamza Ouamna Zhour Madini Younes Zouine Dept. electrical and telecommunication ISET Laboratory Kenitra Morocco

ISBN: (数字)9798350387353

ISBN: (纸本)9798350387360

It appears that the frequency bands used by the current mobile network are becoming increasingly scarce, making it impossible for it to meet the overwhelming demand brought on by the introduction of 5G and the rapidly growing popularity of IOT devices. It is evident that due to spectrum shortage, the traditional method of statically allocating spectrum to particular services or users became systematically inefficient and unsustainable. As a result, it is time for a wireless communication system to emerge that allows multiple users or wireless systems to share radio frequency spectrum in real-time and efficiently. It's DSS ( dynamic spectrum sharing), a revolutionary approach that allows different wireless technologies to dynamically share the same spectrum resources based on demand and usage patterns. This dynamic allocation is typically facilitated by advanced spectrum management techniques and intelligent algorithms that we are going to provide in this article in addition to the challenges that this technology has to face.

关键词： Wireless sensor networks 5G mobile communication Scheduling algorithms Reviews Heuristic algorithms Dynamic scheduling Frequency measurement sensors Security Radio spectrum management

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Offline Pose Correction with High Uncertainty GNSS and Traffic Light Observations on Urban Roads

Offline Pose Correction with High Uncertainty GNSS and Traff...

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international conference on Control, Automation and Systems ( ICCAS)

作者： Soohyun Cho Woojin Chung Department of Mechanical Engineering Korea University Seoul Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Localization using onboard sensors installed in vehicles is essential for technologies such as autonomous driving and HD map creation. Localization with systems composed of low-cost sensors is receiving attention. Offline computation-based localization can be used in applications such as SLAM for HD map creation and environmental change detection. These applications require accurate localization and precise feature detection. However, low-cost sensors produce data with high uncertainty. In the case of GNSS, buildings around urban roads can cause significant errors. In this paper, we propose offline pose correction for vehicles driving on urban roads, taking into account the inaccuracy of the data. The proposed pose correction overcomes data uncertainty by reflecting the structural features of road intersections. Validation was conducted using GNSS, odometry, and traffic light observations collected from drives on urban roads.

关键词： Location awareness Global navigation satellite system Uncertainty Simultaneous localization and mapping Roads Green products sensor systems sensors Odometry Optimization

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Energy Harvesting and Machine Learning Techniques for Internet of Things applications: A Review

Energy Harvesting and Machine Learning Techniques for Intern...

引用

Computing, Sciences and Communications (ICCSC), international conference on

作者： Nutan Tanwar Rajiv Dey Pradeep Kumar Arya Electronics and communication department BML Munjal University Gurugram Haryana Electronics and communication department Guru Ghasidas University Bilaspur India Computer engineering department Bennett University Noida India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353655

The powerful platform that connects both the physical and digital realms is called the Internet of Things, or IoT. The standard of life has increased due to the current developments in Internet of Things (IoT) technologies, which have also enhanced human-technology engagement. The low expenses for positioning, remote availability, and intelligent operation of IoT nodes and sensors are the most important characteristics that propel the IoT's broad acceptance and rapid expansion in the ecological, health, and commercial domains. To solve the matter of energy shortages, energy harvesters, or EHs, are necessary for self-sustaining Internet of Things nodes. In this paper, an extensive analysis of machine learning (ML) techniques used in conjunction with EH-powered Internet of Things (IoT) devices to estimate and manage energy availability. The authors examined the machine learning techniques based on its applications, advantages and limitations on the basis of recent literature.

关键词： Maximum likelihood estimation Reviews Machine learning sensor phenomena and characterization Propulsion Internet of Things Energy harvesting Standards Intelligent sensors

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Design of a Broadband LNA Based on Various Distributed-Element Microwave Filters With Semi-Distributed Notch Filtering for Interference Rejection

Design of a Broadband LNA Based on Various Distributed-Eleme...

引用

Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Faycal El Hardouzi Mohammed Lahsaini Electronics Communication Systems and Energy Optimization Group (OPTIMEE) Faculty of Sciences Moulay Ismail University Meknes Morocco

ISBN: (数字)9798350309508

ISBN: (纸本)9798350309515

In this paper, we have modeled a low-noise amplifier that we have adapted using a multisection filter at the input, a distributed-element bandpass coupled-resonator filter at the output, and a third notch filter for interference rejection. Results show that the amplifier is unconditionally stable over the entire [1.8-3] GHz band. In addition, the gain is satisfactory, and the reflection coefficients S 11 and S 22 at the input and output are low. This modeled amplifier can be integrated into systems dedicated to Wi-Fi, while also offering possibilities for use in other applications such as wireless communications, wireless sensor technologies, telemetry systems, and remote monitoring devices.

关键词： Band-pass filters Wireless communication Matched filters Wireless sensor networks Broadband amplifiers Resonator filters Resonant frequency

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Real-Time Environmental Monitoring: IoT Integration and Remote Access via Raspberry Pi and VNC Viewer

Real-Time Environmental Monitoring: IoT Integration and Remo...

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Cyber Physical Systems, Power Electronics and Electric Vehicles (ICPEEV), international conference on

作者： L V Suresh Kumar T S L V Ayyarao Dept. of EEE GMR Institute of Technology Rajam India

ISBN: (数字)9798350388664

ISBN: (纸本)9798350388671

The growing concerns over air quality and environmental pollution necessitate advanced real-time monitoring systems capable of providing accurate environmental data. This paper introduces a scalable framework for real-time environmental sensing using the Raspberry Pi as the core processing unit. The system integrates multiple sensors: the DHT-11 for humidity and temperature, and the MQ-2 is a Smoke detecting sensor, and MQ-135 for detecting gases such as methane, carbon dioxide, and ammonia. This integration allows for continuous monitoring and data acquisition essential for both urban and industrial applications. The system's performance is evaluated based on accuracy, response time, and reliability under various conditions, demonstrating its effectiveness in delivering real-time, precise measurements. Its cost-efficiency and scalability make it suitable for both large-scale urban monitoring networks and localized industrial environments. Additionally, the system's flexibility in sensor integration and data processing capabilities provides a robust foundation for future advancements in environmental monitoring technologies. This work advances the field of IoT-based environmental sensing by addressing the challenges of sensor integration and real-time data processing on a cost-effective platform like the Raspberry Pi, contributing to improve environmental monitoring and public health initiatives.

关键词： Temperature sensors Temperature measurement Temperature distribution Accuracy Humidity Real-time systems sensor systems sensors Environmental monitoring Reliability

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Design and Implementation of sensor-Based Trapezoidal Control of BLDC Motor Based on XMC-7200 Microcontroller for EV Application

Design and Implementation of Sensor-Based Trapezoidal Contro...

引用

Computer, Electronics & Electrical Engineering & their applications (IC2E3), international conference on

作者： Chirag Jhawar Udaya Bhasker Manthati Prashant Abhishek Department of Electrical Engineering National Institute of Technology Warangal India Infineon Technologies. Bengaluru India

ISBN: (数字)9798350388534

ISBN: (纸本)9798350388541

Nowadays with the exponential growth in technology efficiency is a very critical aspect of any electrical drive system. Using BLDC motors in place of conventional AC induction motors and brushed DC motors can improve efficiency and save energy. In this paper implementation of speed control of brushless DC motor using hall effect sensors with PI controller using XMC 7200 MCU for electric vehicle-type application has been proposed. Block commutation or six-step commutation or trapezoidal control technique is used for the commutation of the phases. This method is straightforward and cost-effective from the implementation of a hardware point of view. A simulation study and hardware implementation have been carried out for this scheme.

关键词： Microcontrollers Commutation Simulation Velocity control Motors Electric vehicles Stability analysis Hardware Real-time systems sensors

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Explainable Spatio-Temporal Graph Modeling 26th

Explainable Spatio-Temporal Graph Modeling

引用

26th international conference on Discovery Science, DS 2023

作者： Altieri, Massimiliano Ceci, Michelangelo Corizzo, Roberto Department of Computer Science University of Bari Aldo Moro Bari Italy Department of Knowledge Technologies Jožef Stefan Institute Ljubljana Slovenia Department of Computer Science American University WashingtonDC20016 United States

ISBN: (纸本)9783031452741

Explainable AI (XAI) focuses on designing inference explanation methods and tools to complement machine learning and black-box deep learning models. Such capabilities are crucially important with the rising adoption of AI models in real-world applications, which require domain experts to understand how model predictions are extracted in order to make informed decisions. Despite the increasing number of XAI approaches for tabular, image, and graph data, their effectiveness in contexts with a spatial and temporal dimension is rather limited. As a result, available methods do not properly explain predictive models’ inferences when dealing with spatio-temporal data. In this paper, we fill this gap proposing a XAI method that focuses on spatio-temporal geo-distributed sensor network data, where observations are collected at regular time intervals and at different locations. Our model-agnostic method performs perturbations on the feature space of the data to uncover relevant factors that influence model predictions, and generates explanations for multiple analytical views, such as features, timesteps, and node location. Our qualitative and quantitative experiments with real-world forecasting datasets show the effectiveness of the proposed method in providing valuable explanations of model predictions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： sensor networks

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A Way of Optimization of Wireless sensor Network using TSCH

A Way of Optimization of Wireless Sensor Network using TSCH

引用

Advance Computing and Innovative technologies in Engineering (ICACITE), international conference on

作者： A R Aravind Manju Prajapati E Arunkumar Rakesh Kumar Himanshu Kumar S P V Subba Rao Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science & Engineering (cs and e) IES College of Technology Bhopal M.P India Department of Electronics and Communication Engineering Karpagam College of Engineering Department of Computer Engineering & Applications GLA University Mathura Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and Technology Hyderabad

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

Within ad hoc wireless networks, TimeSynchronized Channel Hop (TSCH) is a potential method for interference-free and collision-free communication, especially in the setting of wireless sensor networks, car networks, and networks containing robots or drones. Even though TSCH and its versions work well, they need centralized planning to keep the time-frequency sliding system in place. This leads to a restricted usage of time-frequency slots and slow convergence, especially when there is node change or movement. Using the idea of pulse-coupled oscillators, the protocol pairs distributed synchronization or desynchronization methods at the MAC layer to coordinate nodes to perform coordinated signal packet broadcasts over all available channels. Afterwards, peer-to-peer swap requests and acknowledgements between ongoing emitter in neighboring channels result in autonomous channel moving. Extensive evaluation against TSCH and the power source Successful It MAC (EM-MAC) protocol suggests that DT-SCS is a strong contender for centralized multi-channel MAC layer coordination due to its quick convergence, which refers strong connectivity, and high bandwidth utilization even in the midst of interference alongside hidden nodes.

关键词： Wireless sensor networks Time-frequency analysis Protocols Wireless networks Media Access Control Peer-to-peer computing Synchronization

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Fuzzy K-means clustering (FKmC) to maximize the Energy Efficiency in sensor-Enabled Internet of Things 4

Fuzzy K-means clustering (FKmC) to maximize the Energy Effic...

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4th IEEE international conference on Computing, Power and Communication technologies, GUCON 2021

作者： Kashyap, Pankaj Jaiswal, Ankita Kumar, Manoj School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi110067 India

ISBN: (纸本)9781728199511

With recent growth of smart devices, wireless green communication is promising solution to improve the network performance, stability and robustness in the Internet of Things (IoT) networks. Clustering is one the best candidate for network partition which enables energy efficient mechanism for data gathering and transmission from sensor enabled IoT nodes, which also improve the quality of service underlying heterogeneous systems in IoT networks. Mostly, researchers proposed clustering approach in the regard of belongings of nodes to cluster or not. In real scenario, nodes has fuzzy relationship with clsuters, in this regard, we present Fuzzy K-means clustering (FKmC) algorithm to form balanced clustering, which divide the network into disjoint clusters focuses on efficient energy consumption in the IoT network. The work proposed soft clustering (FKmC) for better clusters using the membership parameter of sensor nodes and residual energy of sensor nodes. Simulation work is done in three phases;first phase show the effective formation of cluster between proposed FKmc and state-of-art algorithms, Second and third phase of the simulation are performed and found that FKmC outperforms in terms of network lifetime and energy consumption. © 2021 IEEE.

关键词： Internet of things

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Multi-LiDAR-Inertial Odometry Combined with Vehicle Kinematics for Autonomous Buses

Multi-LiDAR-Inertial Odometry Combined with Vehicle Kinemati...

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Advanced Information, Mechanical Engineering, Robotics and Automation (AIMERA), IEEE international conference on

作者： Tao Song Ying Zheng Pengcheng Wang Xinkai Wu School of Transportation Science and Engineering Beihang University Beijing China Robint Technologies Company Ltd. Beijing China School of Cyber Science and Technology Beihang University Beijing China

ISBN: (数字)9798350343335

ISBN: (纸本)9798350343342

The application of multi-LiDAR setup in autonomous buses is becoming increasingly widespread. However, challenges in real-world applications of multi-LiDAR SLAM remain largely unexplored. This paper introduces a multi-LiDAR-inertial odometry algorithm that utilizes vehicle kinematics to improve positioning accuracy and reliability. First, we introduce a sensor fusion method that synchronizes and integrates data from point cloud, IMU, and wheel encoder in the shortest possible time intervals, using IMU data to correct point cloud distortions. Subsequently, we developed a multi-sensor fusion odometry system combining multi-LiDAR, IMU, and vehicle wheel encoder data. Finally, leveraging the odometry’s results, we generated a comprehensive global point cloud map. The evaluation of the proposed method in real-world scenarios demonstrates its capability to achieve high-precision odometry data and state-of-the-art performance.

关键词： Point cloud compression Accuracy Laser radar Urban areas Wheels Kinematics sensor fusion Odometry Vehicle dynamics Autonomous vehicles

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