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An Overview of Adaptive Network Control in the Internet of Things: Machine Learning Methods for Optimizing Traffic and Dynamic Resource Management

An Overview of Adaptive Network Control in the Internet of T...

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Data Science and Business systems (ICDSBS), International conference on

作者： A Karthikeyan J Joel Department of Electronics and Communication Engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai Department of Computer Science and Engineering RMK Engineering College Chennai

ISBN: (数字)9798331585600

ISBN: (纸本)9798331585617

The Internet of Things (IoT) ecosystem has witnessed exponential growth, making network settings complex and dynamic. These challenges in energy efficiency, traffic, and resource allocation have already made adaptive network control an indispensable instrument for Internet of Things (IoT) systems. The survey provides a comprehensive overview of adaptive network control techniques, particularly those based on ML algorithms to maximize traffic handling and dynamic resource allocation. Focusing on Internet of Things (IoT) use cases such as edge computing, sensor networks, and heterogeneous device management, the research examines a wide variety of ML algorithms, including supervised, unsupervised, and reinforcement learning. The study shows that network scaling using ML-based methods will be stable and load-balanced and reduce latency continuously. Here adaptive resource management is explored with reinforcement learning (RL) methods that can alter on-demand storage, processing and bandwidth to match the dynamic requirements. It says federated learning provides a way to optimize decentralized systems without compromising user data while making full use of distributed resources. Recent studies from the wide spectrum of ML applications provide case studies and experimental findings for increasing fault tolerance, reducing energy consumption, and improving Quality of Service (QoS) in IoT networks. Enabling flexible, efficient, and sustainable IoT networks, this study presents the transformative potential of machine learning. Other important research issues identified include scalable algorithms, real-time decision-making abilities, and high security. Suggestions for future work reveals the area of hybrid ML models, 6G AI convergence and development of light weight algorithms that can be run in low power Internet of Things devices. This work aims to provide a foundation for researchers and practitioners to use machine learning for advanced network control in the context of

关键词： Adaptive systems Machine learning algorithms Federated learning Scalability Heuristic algorithms Reinforcement learning Quality of service Dynamic scheduling Internet of Things Resource management

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A High-Performance Two-Stage OTA for Low Frequency Signal Amplification in Power Constrained systems 6

A High-Performance Two-Stage OTA for Low Frequency Signal Am...

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6th International conference on Devices for Integrated Circuit, DevIC 2025

作者： Tripathy, Mrunmayee Sahoo, Rashmi Rekha Charan Bhuyan, Kanhu Odisha University of Technology and Research School of Electronic Sciences Bhubaneswar India

ISBN: (纸本)9798350391107

This paper introduces a high-performance two-stage operational transconductance amplifier (OTA) designed to achieve superior stability and noise performance while operating under stringent power constraints. Existing OTA designs struggle with stability, power efficiency, and noise suppression trade-offs, making them less effective for precision analog applications. The proposed OTA addresses these limitations through an advanced transconductance-biasing approach and optimized compensation techniques to ensure a high phase margin, reduced distortion, and a robust gain-bandwidth product (GBW). Implemented in 90-nm CMOS technology with an 800mV supply voltage, the OTA is optimized for applications such as health monitoring, wearable devices, and low-power sensor networks, where energy efficiency and signal fidelity are critical. The design effectively tackles key challenges such as noise suppression, power efficiency, and precise low-frequency signal amplification. Simulation results obtained using Cadence Spectre demonstrate a common-mode gain of 89 dB, a GBW of 1.28 MHz, and a phase margin of 63°. Additionally, the OTA achieves a common-mode rejection ratio (CMRR) exceeding 100 dB and an input-referred noise of 17 pV/√Hz, with a power dissipation of just 1.9 μW and a Power Supply Rejection Ratio (PSRR) of 90 dB. These results underscore the OTA's ability to amplify very low-frequency signals with high precision, making it an ideal solution for power-constrained systems requiring reliable and accurate performance. Despite advancements in OTA architectures, prior research has highlighted significant challenges in achieving high gain and low noise while maintaining an optimal trade-off between bandwidth and stability. Here the proposed OTA presents a novel approach that balances stability, gain, bandwidth, and power efficiency. © 2025 IEEE.

关键词： CMOS integrated circuits

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Integrated Railway Infrastructure Optimization and Control System: Leveraging IoT for advanced Railway Management and Monitoring

Integrated Railway Infrastructure Optimization and Control S...

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Electronics, Computing, Communication and Control Technology (ICECCC), International conference on

作者： Husna Tabassum Sahana S Samreen Hunagund Swati Shrikanth Santolli Syed Abdul Rehman Najmusher H Computer Science & Engineering HKBK College of Engineering Bangalore India

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371819

The Railway Track Tracer technology for Creature Detection is a technology that detects fractures in railway tracks. This method will assist in preventing numerous train accidents. This device routinely checks railway rails with a camera and DC motors to detect fractures and take appropriate action to avoid accidents. The Internet of Things is the most studied field, and its applications are endless. Internet of Things (IOT) has been implemented to provide up-to-date updates on railway management. In this mode, an IR sensor is used to check the availability of the platform. This system is used to update the platform availability to the upcoming train to avoid or to prevent accidents by the usage of Zigbee, which acts as wireless communication from station to train and from train to station and detects fire and automatic engine detachment. To update the platform availability. There has been an upsurge in railway accidents caused mainly by track quandaries. That might be a misalignment, an obstacle, a crack in one of the track's sides, or some other fault with the track. So, keeping track of all these difficulties is a time-consuming chore for a person. The scope of the paper encompasses detecting the cracks on rail tracks using network signals - checking the platform availability, Zigbee for the communication, fire sensor for detecting the fire ultrasonic sensors, and Nodemcu can be used. The Railway Track Tracer technology for Creature Detection is a technology that detects fractures in railway tracks. This method will assist in preventing numerous train accidents.

关键词： YOLO Rails Wireless communication Zigbee Rail transportation Real-time systems Internet of Things

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Detailed characterization of a hyperspectral snapshot imager for full-field chromatic confocal microscopy

Detailed characterization of a hyperspectral snapshot imager...

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conference on Optics and Photonics for advanced Dimensional Metrology

作者： Hahn, Robin Haemmerling, Freya-Elin Haist, Tobias Fleischle, David Schwanke, Oliver Hauler, Otto Rebner, Karsten Brecht, Marc Osten, Wolfgang Univ Stuttgart Inst Tech Opt Pfaffenwaldring 9 D-70569 Stuttgart Germany Twip Opt Solut GmbH Stammheimer Str 10 D-70806 Kornwestheim Germany Reutlingen Univ PA&T Altenburgstr 150 Reutlingen Germany

ISBN: (数字)9781510634770

ISBN: (纸本)9781510634770

Hyperspectral imaging opens a wide field of applications. It is a well established technique in agriculture, medicine, mineralogy and many other fields. Most commercial hyperspectral sensors are able to record spectral information along one spatial dimension in a single acquisition. For the second spatial dimension a scan is required. Beside those systems there is a novel technique allowing to sense a two dimensional scene and its spectral information within one shot. This increases the speed of hyperspectral imaging, which is interesting for metrology tasks under rough environmental conditions. In this article we present a detailed characterization of such a snapshot sensor for later use in a snapshot full field chromatic confocal system. The sensor (Ximea MQ022HG-IM-SM5X5-NIR) is based on the so called snapshot mosaic technique, which offers 25 bands mapped to one so called macro pixel. The different bands are realized by a spatially repeating pattern of Fabry-Perot filters. Those filters are monolithically fabricated on the camera chip.

关键词： hyperspectral imaging hyperspectral sensor snapshot sensor chromatic confocal microscopy single-shot metrology

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advanced Mathematical Modeling and Control Strategies for Autonomous Drone systems

Advanced Mathematical Modeling and Control Strategies for Au...

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International Carpathian Control conference (ICCC)

作者： Cosmin Rus Eduard Lupulescu Monica Leba Marius Risteiu Departament of Automation Computers Electrical and Power Engineering University of Petrosani Petrosani Romania Doctoral School University of Petrosani Petrosani Romania

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

This paper explores the mathematical modelling and simulation of drones, focusing on both low-level and high-level control aspects. The low-level control involves altitude maintenance and stabilization, alongside disturbance compensation, essential for ensuring stable flight. At the high-level control, the research addresses compensating for air currents, drift correction, obstacle avoidance, localization, mapping, navigation to predefined points, returning to the take-off position (return to home), and person tracking. Additionally, it highlights the inherent limitations in drone usage, including restricted weight capacity, limited processing power, a constrained number of sensors, short battery life, rapid dynamics requiring electronic stabilization, continuous motion of the drone, and safety concerns. The study emphasizes the intricate interplay between mathematical models and control strategies to manage these control objectives and constraints. It delves into the development of mathematical models representing drone dynamics and sensor data fusion techniques. Simulation environments are utilized to validate and optimize control algorithms, replicating real-world scenarios to ensure reliable and robust drone performance. The paper aims to address these challenges by proposing mathematical modelling techniques and control strategies. By integrating sophisticated algorithms with limited hardware resources, it seeks to improve the efficiency and autonomy of drones while overcoming constraints. Ultimately, the research endeavours to contribute to the advancement of drone technology, enabling enhanced capabilities for various applications while ensuring safety and reliability.

关键词： Tracking Navigation Heuristic algorithms Dynamics sensor fusion Mathematical models Hardware

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Revolutionizing Gas Safety: The IoT Gas Detector with Automatic Regulator Control

Revolutionizing Gas Safety: The IoT Gas Detector with Automa...

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Innovative Practices in Technology and Management (ICIPTM), International conference on

作者： Kumar Keshamoni Ganna Koteswara Rao Bharatha Satheesh Pabbala Priyanka Department of ECE Vaagdevi Engineering College Warangal Telanagana India Department of ECE Vaagdevi College of Engineering Warangal Telanagana India

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

The IoT Gas Detector, a groundbreaking innovation, integrates the ESP32 microcontroller with the Blynk platform to redefine environmental monitoring. This advanced device offers real-time gas detection and monitoring across various applications, ranging from residential safety to industrial settings. Leveraging the ESP32's robust processing capabilities and wireless connectivity, the system interfaces with gas sensors for carbon monoxide (CO), methane (CH4), and Liquefied Petroleum Gas (LPG). The ESP32 continuously collects and analyzes sensor data, ensuring swift responses to gas leaks or irregularities. The Blynk platform is the cornerstone, providing centralized data visualization, remote monitoring, and control. Users can access the gas detector via the Blynk mobile app or web dashboard, enabling real-time monitoring and instant ***, the system supports historical data logging for trend analysis and long-term environmental monitoring. Integrating the IoT Gas Detector with ESP32 into the Blynk platform marks a significant leap forward in gas monitoring technology, combining cutting-edge hardware with user-friendly interface design. This integration enables real-time remote gas detection, enhancing safety across various environments. The paper discusses the system's capabilities and highlights its potential to foster a safer and more connected world.

关键词： Wireless communication Wireless sensor networks Technological innovation Regulators Detectors Real-time systems Safety

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Experimental Study of a LoRa Based Wireless sensor Network for Low Power Localization in an Outdoor Environment

Experimental Study of a LoRa Based Wireless Sensor Network f...

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Electronics, Energy and Measurement (IC2EM), International conference on

作者： Abdelhafid Tobbal Billel Bengherbia Anis Bouziani Youcef Cherifi Research Laboratory in Advanced Electronics Systems LSEA University Yahia Fares of Medea Medea Algeria

The Internet of Things (IoT) and Wireless sensor Network (WSN) have transformed industries by highlighting their crucial roles in sensing, communication, and data-driven decisions. One paramount feature in WSN is localization, enabling precise positioning of devices in real-world applications. Global Positioning systems (GPS) have long been the mainstay of high-precision localization, but their high energy consumption is a significant obstacle to their seamless integration with low-power devices. In the quest for suitable solutions, Low Power Wide Area Networks (LPWAN) have emerged as key players, providing energy-efficient connectivity. However, these advances raise questions about the localization accuracy within these networks. In this paper, we present the implementation of WSN based on Long Range (LoRa) technology to estimate the position of an object in an outdoor environment. We took advantage of LoRa technology to collect Received Signal Strength Indicator (RSSI) measurements over a long distance. An Artificial Neural Network (ANN) is then trained on a collected dataset to estimate the 2-dimensional position of the object. The results show an estimate of the position with an average absolute error of 40.5 meters in an area of 360 meters by 360 meters. A web interface is made with Node-Red to monitor the position of the mobile object.

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Cam-Driven Frequency Up-Conversion Mechanism For Kinetic Energy Harvesting

Cam-Driven Frequency Up-Conversion Mechanism For Kinetic Ene...

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Micro and Nanotechnology for Power Generation and Energy Conversion applications (PowerMEMS)

作者： Heng Zhao Tianyi Tang Yunfei Li Mingqi Mei Huicong Liu School of Mechanical and Electrical Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou CHINA State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin CHINA

ISBN: (数字)9798350380200

ISBN: (纸本)9798350380217

This paper proposes an ocean wave energy harvester (WEH) with a cam-driven frequency up-conversion mechanism. It utilizes a planar pendulum structure to achieve motion response to ultra-low-frequency wave excitation and then converts the mechanical energy of the pendulum into high-frequency and high-power electrical energy output through the cam-driven frequency upconversion mechanism. WEH’s superior design enables high-power output even under excitation below 1 Hz. At the excitation frequency of 0.75 Hz and resistance load of $20 \Omega$, the maximum power output can reach 461.4 mW. Due to its high output power, the WEH can be integrated into the ocean observation buoy to power the sensors, thereby enabling long-term, unattended operation of the buoy in remote offshore areas.

关键词： Temperature sensors Resistance Ocean waves Frequency conversion sensor systems sensors Power systems Wave energy conversion Power generation Ocean temperature

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Real-Time Monitoring and Surveillance in Hazardous Environments using IoT-enabled Robotics

Real-Time Monitoring and Surveillance in Hazardous Environme...

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Advances in Computing, Communication and Networking (ICAC2N), International conference on

作者： Inderjeet Singh Shree Gaayathri V Vipin Kumar T. Aarthy T. Akilan Vishnu Sharma Dept. of ECE Chandigarh College of Engineering and Technology Chandigarh India Department of CSE RMK Engineering College Chennai India Dept. of IQAC Amity University Kolkata West Bengal India Department of CSE Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai India Department of CSE ITS Engineering College Greater Noida U.P.

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

This research article presents an innovative approach to surveillance technology utilizing advanced Internet of Things (IoT) capabilities in a robot design, specifically engineered for hazardous and domestic environments. The proposed robot is equipped with cutting-edge cameras, sensors, and an Arduino Nano Microcontroller, alongside WIFI/Bluetooth modules that provide remote control functionality through smartphones or personal computers. This allows users to conduct surveillance tasks safely and effectively in areas where human access is difficult or dangerous. In domestic settings, the robot can transmit video data to users in real-time, while the wireless camera enables users to access video streams in both daylight and night-time conditions. Overall, this system is both reliable and efficient, providing users with a robust solution for their surveillance needs, whether for domestic or defense applications.

关键词： Wireless communication Wireless sensor networks Surveillance Robot vision systems Streaming media Cameras Real-time systems sensors Internet of Things Smart phones

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Public Vehicle Passenger Counting System using Infrared Imaging with Data Analytics

Public Vehicle Passenger Counting System using Infrared Imag...

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IEEE Region 10 International conference TENCON

作者： John Michael B. Besmonte Jherome Ivan C. Dela Cueva Justito Vicente A. Jimenez III Danzkyle Dominic D. Valenzuela Maria Leonora C. Guico Jan Kevin A. Galicia Department of Electronics Computer and Communications Engineering Ateneo de Manila University Quezon City Philippines

ISBN: (数字)9798350350821

ISBN: (纸本)9798350350838

The research was dedicated to devising and implementing a comprehensive monitoring system tailored specifically for the e-jeeps operating within the confines of Ateneo de Manila University. Leveraging advanced GPS sensors, this system enabled the real-time tracking of e-jeepneys while simultaneously providing crucial insights into their speed and estimated time of arrival at various points across the campus. the research unearthed intriguing findings regarding the relationship between passenger count and environmental conditions. While a minimal correlation was observed, it was noted to be contingent upon the specific time of day, indicating potential variations in passenger behavior influenced by diurnal factors. In order to streamline data management and visualization, the researchers capitalized on the robust infrastructure provided by various Google applications and cloud services. This integration facilitated the seamless uploading and synthesis of sensorderived data, empowering the creation of a dynamically updated dashboard providing comprehensive insights into e-jeepney operations The study represents a significant milestone in the realm of transportation management, successfully culminating in the development and deployment of a sophisticated monitoring system.

关键词： Cloud computing Correlation Web services Data visualization sensor systems Real-time systems Internet sensors Monitoring Global Positioning System

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