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International conference on Computing Communication control and Automation (ICCUBEA)

作者： Suvarna Patil Rajashree S. Salunke Vedant S. Sapkale Rohan H. Sawant Saee A Shinde Computer Department Dr.D.Y.Patil Institute Of TechnolgyPimpri Pimpri Pune

ISBN: (数字)9798350391770

ISBN: (纸本)9798350391787

In response to the growing challenges of waste management, particularly in urban areas, this study presents an innovative approach leveraging deep learning techniques for automated waste management. Traditional waste management systems often struggle with inefficiencies in waste sorting and processing, leading to environmental pollution and resource wastage. To address these issues, this research proposes an automated system that utilizes deep learning algorithms to classify waste items accurately. By training deep neural networks on large datasets of waste images, the system can categorize waste items into predefined classes, enabling automated sorting processes. Integration with robotic systems allows for the implementation of real-time waste sorting and processing, reducing the need for manual intervention and improving overall efficiency. The proposed approach aims to enhance waste management practices, promote recycling efforts, and contribute to environmental sustainability. Through the adoption of advanced technologies such as deep learning, this automated waste management system offers a promising solution to the challenges of modern waste management.

关键词： Waste management Deep learning Training Urban areas Real-time systems sensor systems Recycling sensors Sustainable development Sorting

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Enhancing Smart Home Security systems through the Integration of IoT Devices: A Comprehensive Approach

Enhancing Smart Home Security Systems through the Integratio...

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International conference on Contemporary Computing and Informatics (IC3I)

作者： Pinkal Jain Ajay Lala Department of CSE Gyan Ganga College of Technology Jabalpur Gyan Ganga College of Technology Jabalpur

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Technology has taken center stage in today’s fast-paced world, where it powers nearly every aspect of daily life. The concept of remotely connecting and monitoring physical items (things) via the Internet is known as the Internet of Things (IoT). The need to safeguard our loved ones and possessions has increased due to the rising crime rate. These circumstances can be resolved by taking advantage of the newest features that modern technology has to offer, such as IOT, which enables seamless data connection, and remote-control capability, which facilitates the automation of security procedures. Security can be automated by creating an application for the Raspberry $\mathbf{P i}$ and ATmega 328 microcontroller that uses various sensors, including motion and PIR (passive infrared) sensors, to detect any intruders in the home. When an intruder is detected, an alarm is set off, and the homeowner and notification messages are sent. This idea can be appropriately applied to our home to make it safer, smarter, and more automated. The overall design of a wireless, low-cost home automation system (HAS) is shown in this project. The system’s smart home idea raises the bar for living at home. The PIR motion detector sensor in front of the house detects the presence of people, sends a message to the owner, and allows him to observe the person through the front camera. The web portal allows access to the camera and allows control over the light, fan, door lock, and alarm. The system’s user-friendly interface, affordable construction, and simplicity of installation made it ideal for controlling household electrical appliances and devices. The owner can control the electrical appliances based on their priorities. Depending on the owner’s priority, those who successfully authenticate can use the house appliances and unlock the door by typing their password on the keypad. Our proposed method achieved an impressive accuracy of $98.7 \%$, demonstrating superior efficiency compared to c

关键词： Wireless communication Wireless sensor networks Microcontrollers Smart homes Passwords Cameras Internet of Things Security Electrical products Portals

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Robust sensor Fusion Algorithms Against Voice Command Attacks in Autonomous Vehicles 20

Robust Sensor Fusion Algorithms Against Voice Command Attack...

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20th IEEE International conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom)

作者： Guan, Jiwei Zheng, Xi Wang, Chen Zhou, Yipeng Jolfaei, Alireza Macquarie Univ Dept Comp Sydney NSW Australia CSIRO Data61 Sydney NSW Australia

ISBN: (纸本)9781665416580

With recent advances in autonomous driving, voice control systems have become increasingly adopted as human-vehicle interaction methods. This technology enables drivers to use voice commands to control the vehicle and will be soon available in advanced Driver Assistance systems (ADAS). Prior work has shown that Siri, Alexa and Cortana, are highly vulnerable to inaudible command attacks. This could be extended to ADAS in real-world applications and such an inaudible command threat is difficult to detect due to microphone nonlinearities. In this paper, we aim to develop a more practical solution by using camera views to defend against inaudible command attacks where ADAS are capable of detecting their environment via multi-sensors. To this end, we propose a novel multimodal deep learning classification system to defend against inaudible command attacks. Our experimental results confirm the feasibility of the proposed defense methods and the best classification accuracy reaches 89.2%. Code is available at https://***/ITSEG-MQ/sensor-Fusion-Against-VoiceCommand-Attacks.

关键词： advanced driver assistance systems

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Obstacle Collision Warning Using Ultrasonic and LiDAR sensor Fusion

Obstacle Collision Warning Using Ultrasonic and LiDAR Sensor...

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IEEE Region 10 Humanitarian Technology conference (R10-HTC)

作者： Gayatri Gurav P. Balakrishnan Department of Electronics & Communication Engineering Amrita School of Engineering Coimbatore India Department of Electrical & Electronics Engineering Amrita School of Engineering Coimbatore India

Recently, passenger vehicles were equipped with an advanced Driver Assistance system (ADAS) feature in assisting drivers to control the vehicle, which gives an alarming signal about possible dangers. Obstacle collision warning (OCW) uses sensors installed in front of the vehicle to detect distance between the front obstacle and the vehicle, to avoid a collision. In common, the types of sensors used in obstacle detection are camera, radar, ultrasonic sensor, and so on. In this paper, fusion of ultrasonic sensor and Light Detection and Ranging (LiDAR) is proposed, which provides extended range detection and increased accuracy. Hardware implementation of ultrasonic sensor and Leddar M16 LiDAR sensor fusion is carried out using an Arduino UNO controller and for, in vehicle communication controller Area Network (CAN) protocol were used. The outcome of both short and long-distance obstacle detection using ultrasonic and LiDAR are compared.

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Design and Development of Pelletizer Automation using Load control

Design and Development of Pelletizer Automation using Load C...

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Smart Electronics and Communication (ICOSEC), International conference on

作者： K Prabhu S Vijayachitra D Mukila L B Mukesh G Nithesraj Department of Electronics and Instrumentation Engineering Kongu Engineering College Perundurai

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

This research study aims to design and implement an advanced automation system for pelletizers, integrating load control technology to optimize pellet production processes. Pelletizers are widely used in industries such as agriculture, food processing, and pharmaceuticals for converting raw materials into uniform pellets. However, traditional pelletizer systems often lack precise control over load conditions, leading to inefficiencies, inconsistencies, and potential equipment damage. Incorporation of load sensors into the pelletizer system to monitor the load exerted on the pelletizing blades or rollers in real-time. Load sensors will provide accurate feedback on the compression force applied during the pelletization process, enabling precise control and adjustment of pelletizer parameters. Implementation of an intuitive current rating and load to facilitate the controlled automation of pelletizing motors. A controller will provide operators with control options, real-time monitoring of load conditions, status updates, and alarm notifications, ensuring ease of operation and troubleshooting. Development of intelligent control logic and algorithms to optimize pelletization parameters dynamically based on load feedback and quality requirements. The proposed system will be capable of adjusting process parameters in real-time to accommodate variations in raw material properties and production conditions. Incorporation of data logging capabilities to record key process parameters, load profiles, and production metrics over time. Data analysis tools will enable performance evaluation, process optimization, and predictive maintenance scheduling. the paper aims to demonstrate the feasibility and advantages of integrating load control technology into pelletizer systems, leading to enhanced efficiency, precision, and safety in pellet production processes.

关键词： Automation Process control Production Motors Real-time systems Raw materials sensor systems sensors Load flow control Monitoring

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Review on a Smart Solar-Powered Greenhouse system using IoT sensors for Automated Internal Climate control and Crop Monitoring

Review on a Smart Solar-Powered Greenhouse System using IoT ...

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Advancements in Power, Communication and Intelligent systems (APCI), International conference on

作者： Dharunjayavinayak R Charanya G M Jayakumar Department of Electrical and Electronics Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350363289

ISBN: (纸本)9798350363296

Intelligent technology integration into farming practices is a revolutionary development with possibilities for increased production and sustainability. This thorough investigation involves the integration of Internet of Things (IoT) sensors in solar-powered greenhouse systems to facilitate advanced crop surveillance and inner climate control. The synthesis explores the interplay between solar energy and IoT advancements, drawing on reliable sources to elaborate on the advantages and challenges of this innovative farming strategy. This study explores how renewable energy, particularly solar power, may be integrated into greenhouse architecture. It also covers the technical details of installing solar panels, energy storage, and how they work with other energy sources. This article explores how IoT sensors might improve crop surveillance and streamline inner climate control. The final section highlights the emerging trends, navigates through potential obstacles, and highlights the critical importance of intelligent solar-powered greenhouses moving towards the path to sustainable agriculture.

关键词： Surveillance Green products Crops sensor systems Agriculture Internet of Things Sustainable development

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A high-accuracy, low-budget sensor Glove for Trajectory Model Learning 20

A high-accuracy, low-budget Sensor Glove for Trajectory Mode...

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20th International conference on advanced Robotics, ICAR 2021

作者： Denz, Robin Demirci, Rabia Cansev, M. Ege Bliek, Adna Beckerle, Philipp Rueckert, Elmar Rottmann, Nils Institute For Robotics and Cognitive Systems University of Luebeck Luebeck23562 Germany Chair of Autonomous Systems and Mechatronics Friedrich-Alexander-University Department of Electrical Engineering Erlangen-Nürnberg Germany Chair of Cyber-Physical-Systems Montanuniversität Leoben Leoben Austria

ISBN: (纸本)9781665436847

sensor gloves are gaining importance in tracking hand and finger movements in virtual reality applications as well as in scientific research. They introduce an unrestricted way of capturing motion without the dependence on direct line of sight as for visual tracking systems. With such sensor gloves, data of complex motion tasks can be recorded and used for modeling probabilistic trajectories or teleoperation of robotic arms. While a multitude of sensor glove designs relying on different functional principles exist, these approaches require either sensitive calibration and sensor fusion methods or complex manufacturing processes. In this paper, we propose a low-budget, yet accurate sensor glove system that uses flex sensors for fast and efficient motion tracking. We evaluate the performance of our sensor glove, such as accuracy and latency, and demonstrate the functionality by recording motion data for learning probabilistic movement models. © 2021 IEEE.

关键词： Budget control

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Internet of Things Enabled Smart Agriculture Monitoring and control system

Internet of Things Enabled Smart Agriculture Monitoring and ...

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Disruptive Technologies (ICDT), International conference on

作者： Nilesh Bhaskarrao Bahadure Rahul Joshi Deepak Parashar Bhoomi Shah Jagdish Chandra Patni Prasenjeet Damodar Patil Department of CSE School of Technology GSFC University Vadodara Gujarat India Department of CSE Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India Department of CSE Alliance School of Advanced Computing Alliance University Bengaluru India Department of CSE School of Computing MIT Art Design and Technology University Pune

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The Indian economy mainly revolves around the agriculture sector, and it is one of the dominant nations in agriculture. In recent times, traditional methods of agriculture have become more inclined towards automation-based agricul-ture, where the integration of modern technologies such as the Internet of Things, Machine Learning, Artificial Intelligence, and many others are taking the lead. In our proposed system, various sensors relating to agriculture mapping are integrated with the Internet of Things, and the data collected from the sensors, processed through IoT, will be further analyzed using machine learning and suggesting a corrective mechanism based on the data collected. No human intervention is needed; the system is fully automatic, responds within a delay time of 8.1 sec, and produces an accuracy of 94.68 % in predicting the data harvest.

关键词： Smart agriculture Machine learning Lead sensor systems Livestock Internet of Things Disruptive technologies Intelligent sensors Monitoring Farming

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High Sensitivity Submicron Scale Temperature sensor Based on Perovskite Nanoplatelet Lasers

SSRN

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SSRN 2024年

作者： Zhao, Ruofan Tao, Jianxun Xi, Yuying Chen, Jiangzhao Ji, Ting Wang, Wenyan Wen, Rong Cui, Yanxia Chen, Junsheng Lia, Guohui College of Physics and Optoelectronics Key Laboratory of Interface Science and Engineering in Advanced Materials Key lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan030024 China School of Materials Science and Engineering Kunming University of Science and Technology Kunming650093 China Shanxi-Zheda institute of advanced materials and chemical engineering China Nano-Science Center Department of Chemistry University of Copenhagen Universitetsparken 5 CopenhagenDK-2100 Denmark

Submicron scale temperature sensors are crucial for a range of applications, particularly in micro and nanoscale environments. One promising solution involves the use of active whispering gallery mode (WGM) microresonators. These resonators can be remotely excited and read out using free-space structures, simplifying the process of sensing. In this study, we present a submicron-scale temperature sensor with a remarkable sensitivity up to 190 pm/℃ based on a triangular CH3NH3PbI3 nanoplatelet (NPL) laser. Notably, as temperature changes, the peak wavelength of the laser line shifts linearly. This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser. The optical modes are confined within the perovskite NPL, which measures just 85 nanometers in height, due to total internal reflection. Our NPL laser boasts several key features, including a high Q-factor of ~ 2610 and a low laser threshold of about 19.8 µJ cm−2. The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors. This advancement paves the way for significant progress in the development of ultrasmall temperature sensors, opening new possibilities across various fields. © 2024, The Authors. All rights reserved.

关键词： Perovskite

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Mismatch and Offset-Voltage Compensation Technique for Current Excitation Based Resistive sensors interface

Mismatch and Offset-Voltage Compensation Technique for Curre...

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Annual IEEE Northeast Workshop on Circuits and systems (NEWCAS)

作者： Mehreeq Mushtaq Mohammad Idris Wani Sadan Saquib Meraj Ahmad Laxmeesha Somappa Maryam Shojaei Baghini Hadi Heidari Shahid Malik Centre of Sensors Instrumentation and Cyber Physical System Engineering Indian Institute of Technology Delhi National Institute of Technology Srinagar Centre of Sensors Instrumentation and Cyber Physical System Engineering Indian Institute of Technology Delhi New Delhi India School of Engineering University of Glasgow Glasgow UK Department of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

Resistive sensors have been increasingly used in a number of wearable biomedical applications ranging from prosthetic control to electronic skin, thanks to their miniaturized size. However, most resistive sensor systems suffer thermoelectric offset, large baseline resistance, and drift in baseline resistance. In addition, the system should be battery-operated and consume low power. In this paper, we present a pulse current excitation-based half-bridge mixed-signal interface circuit for accurate and high-resolution resistance measurement of resistive sensors. The circuit utilizes synchronous demodulation and a DC-Servo loop to compensate for the offset and mismatch to enhance the accuracy and measurement range. The circuit provides a linear output voltage proportional to the incremental change in sensor resistance. A prototype of the proposed system is developed and tested. The circuit compensates offset-voltage as high as ± 1.4 Volts and the resistance mismatch up to 100 $\mathrm{k}\Omega$ for a supply voltage of 3.3 Volts with an error of less than ± 1%.

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