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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Haris, Muhammad Ubaid, Bilal Bibi, Uzma Said, Ameer Us Saqib, Syed Najm Khan, Shahbaz Tufail, Muhammad Advanced Robotics and Automation Lab National Center of Robotics and Automation Peshawar Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan Institute of Manufacturing Engineering Management University of Engineering and Applied Sciences Swat Swat Pakistan

ISBN: (纸本)9781665464727

This paper presents the Design and Development of IoT Based Weather and Air Quality Monitoring stations that provide weather-related information for agriculture, and aviation climate forecasting purposes. The prototype is made up of an outdoor unit that consistently monitors numerous climatic variables such as temperature, humidity, barometric pressure, wind speed, wind direction, rainfall, and air quality using sensors with high accuracy. The air quality index(AQI) is also calculated using the sensors values which tell us whether the atmosphere is safe or polluted. ESP32(Microcontroller) which has a WiFi module is used to gather and send the sensor data through the Internet of things (IoT) to a ThingSpeak channel (IoT cloud), an internet platform where the data is saved, analyzed and read the data remotely. The weather station makes use of photovoltaic power and a rechargeable lead-acid battery to sustain the system. This paper also discusses the obvious strengths and shortcomings of the system and suggests plausible upgrades to assist the system in obtaining higher and long-term performance. © 2023 IEEE.

关键词： Internet of things

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Evaluation of complaint damper for assessing its effectiveness and efficiency through the utilization of topology optimization

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Interactions 2024年第1期245卷 1-17页

作者： Emmanual, L. Narayanan, V. R. Shankara Mukesh, G. Sibi, M. Vijayan, V. Department of Robotics and Automation Easwari Engineering College Tamil Nadu Chennai600089 India Department of Mechanical Engineering M.Kumarasamy College of Engineering Thalavapalayam Tamil Nadu Karur639113 India Department of Mechanical Engineering K.Ramakrishnan College of Technology Tamil Nadu Samayapuram Trichy621 112 India

The term 'chatter' is related to the undesirable vibration produced in any equipment under dynamic operating conditions. It has a wide range of negative consequences for both the machine and the components it produces. Vibrations in the process of machining must be minimized as much as feasible. Dampers serve an important function in mitigating the impacts of chatter during machining. Dampers have traditionally been used to support machines and reduce clatter. Dampers are currently made up of numerous pieces that are mechanically joined together to perform the needed task of reducing chatter. To reduce the number of components and mechanical assembly, we use a complaint mechanism that transmits and absorb force, motion, and so on in a single monolithic structure. This paper presents a unique method to construct dampers utilizing a complaint system. A design was created implementing building pieces in a structure that has been topology optimized. The complaint damper was created using Fused Deposition Modeling (FDM). The complaint damper was employed in place of the rubber damper to evaluate performance. The experiments were carried out on a 3D printer (Fractal Twin Dragon) under various operating circumstances. During the experiment, a 1.75 mm diameter PLA spool was used as the feed. The machine attributes were taken into account. The complaint damper was located at the bottom of the machine's leg. The vibrometer VB-820HA contact type was also mounted to the machine leg and measured response that include velocity, acceleration, displacement, and frequency. The acceleration & frequency profile clearly suggest a larger magnitude when the complaint damper is used. When compared to conventional solid damping, The initial runs are at lower federate of 0.6 mm/min shows nearly identical velocity readings between the two dampers. Rubber damping resulted in a maximum displacement of 0.55 mm. The displacement created by the suggested damper is insignificant. even at higher fr

关键词： Fused Deposition Modeling

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Detection of Lower-Limb Motion Using a Kneepad Sensor Based on Textile Strain Sensor 18

Detection of Lower-Limb Motion Using a Kneepad Sensor Based ...

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18th International Conference on Nano/Micro Engineered and Molecular Systems, NEMS 2023

作者： Zou, Xiaoyang Li, Xiaoting Xue, Jiaqi Lai, King Wai Chiu City University of Hong Kong Centre for Robotics and Automation Department of Biomedical Engineering Hong Kong

ISBN: (纸本)9798350333480

The monitoring of the knee joint angle during lower-limb motions is crucial for knee disorders patients and their rehabilitation. However, commonly used methods for lower-limb motion detection, such as inertial measurement units (IMUs) and motion capture systems, have limitations such as drift and high cost. To address these issues, we developed a wearable kneepad sensor using textile resistive strain sensors to measure knee angle during lower-limb motion. The strain sensors change in resistance signals caused by their deformation of them when the knee joint bends. To improve the accuracy of knee angle measurements, an encoder was integrated with kneepad sensor onto a prosthetic limb and used linear mapping method to calibrate the kneepad sensor with the encoder data as the ground truth. The calibrated kneepad sensor achieved an R2 value of 0.956, MAE of 6.15°, and MSE of 64.35 while detecting the knee angle. It was demonstrated that the ability of the kneepad sensor to measure knee angles during two types of lower-limb motions, sit-to-stand (STS) and knee extension. It is shown in this work that this comfortable, wearable kneepad sensor can help detect knee angles during lower-limb motions in various environments and has broad applications in healthcare and robotics. © 2023 IEEE.

关键词： Textiles

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Video Stabilization using RAFT-based Optical Flow

Video Stabilization using RAFT-based Optical Flow

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Ashar, Rana Sadiq, Burhan Mohiuddin, Hira Ashraf, Saniya Imran, Muhammad Ullah, Anayat Control Automotive and Robotics Lab National Centre of Robotics and Automation Rawalpindi Pakistan Balochistan University of IT Engineering and Management Sciences Department of Electronic Engineering Quetta Pakistan

ISBN: (纸本)9781665464727

Video Stabilization is the basic need for modern-day video capture. Many methods have been proposed throughout the years including 2D and 3D-based models as well as models that use optimization and deep neural networks. This work describes the implementation of cutting-edge Recurrent All-Pairs Field Transforms (RAFT) for optical flow estimation in video stabilization. we use a pipeline that accommodates the large motion. It then passes the results to the optical flow for better accuracy. After that, it satisfies the inaccuracies of the optical flow and makes it robust to occlusion, Parallax, and moving objects. Our approach yields better results (visually and quantitatively) compared to other optimization and deep learning-based visual stabilization techniques. © 2023 IEEE.

关键词： Geometrical optics

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Comparative Study of Energy Management Techniques for Solar PV-based Microgrid Systems 6

Comparative Study of Energy Management Techniques for Solar ...

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6th Parul International Conference on engineering and Technology, PICET 2024

作者： Kamagaté, Yaya Shah, Heli Amit Sharma, Sspm B. Electrical Engineering Department Parul University Vadodara India Robotics and Automation Engineering Department Parul University Vadodara India Mechatronics Engineering Department Symbiosis University of Applied Sc Indore India

ISBN: (纸本)9798350369748

In recent years, microgrid systems have gained popularity as reliable, efficient, and clean energy sources for local communities. Among these, solar PV systems stand out as a widely used microgrid variant. However, the intermittent nature of solar power necessitates the incorporation of energy storage solutions to ensure a consistent electricity supply. In this context, batteries and supercapacitors emerge as two prominent options for storing energy in solar PV microgrids. This study leads a comprehensive examination and correlation of three distinct solar PV-based microgrid configurations: solar PV system (PVS), solar PV with battery system (PVBS), and solar PV with both battery and supercapacitor system (PVBSS). Employing MATLAB/Simulink, the analysis centers on their technical capabilities, particularly emphasizing energy management. The simulation results demonstrate that incorporating battery storage enhances the performance of the PVS microgrid, ensuring the stability of the DC bus voltage and thus balancing energy production and consumption. Furthermore, the PVBSS configuration exhibits superior performance through its capacity to deliver high power with rapid response times, consequently extending the battery lifespan. This investigation underscores the critical role of energy storage solutions in enhancing solar PV microgrids' effectiveness and overall performance. © 2024 IEEE.

关键词： Battery storage

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Secrecy Performance Review for IoT-based Cognitive Farming System

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Recent Patents on engineering 2024年第7期18卷 66-75页

作者： Chopra, Khyati Alam, M. Afshar Department of CSE Jamia Hamdard University New Dehli India University School of Automation and Robotics GGSIPU New Delhi110032 India Department of Computer Science and Engineering Jamia Hamdard University New Delhi110062 India

Smart farm management has complex challenges;therefore, there is a need to improve the overall adaptability, profitability, and environmental soundness of the farming systems. Agricultural production can be enhanced with the help of IoT-based cognitive tools. The rapid increase in IoT-based smart systems has raised critical concerns about efficiently utilizing the wireless spectrum. To drastically bring the improvement in the utilization of the wireless spectrum, cognitive radio (CR) has emerged as an effective solution. The inherent openness and broadcast nature of the wireless medium have given rise to many security issues in cooperative networks. Information-theoretic security or physical layer security (PLS) is evolved as an efficacious wireless prototype for reliable transmissions to avert the eavesdropper from expropriating transmittal data on the wireless connections. Security is the key factor in these networks as they are exposed and active in be-havior, thus, are susceptible to fraudulent activities. In this patent study, we investigated the performance of the CR system in terms of secrecy and also examined the system in terms of diversity receipt and selection of relay. The secrecy outcome of channel state information at the sender was also studied. The detrimental effects of fading in cooperative networks were also extensively discussed. Cooperative diversity was examined by deploying MRC and SC strategies at receptors. It has been deduced that CSI knowledge at the sender also has an eloquent concussion on the secrecy of the cognitive system. © 2024 Bentham Science Publishers.

关键词： Cognitive radio

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Odometry and Inertial Sensor-based Localization of a Snake Robot

Odometry and Inertial Sensor-based Localization of a Snake R...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Shahid, Ramsha Baloch, Anam Tahir, Humayun Ullah, Anayat National Centre of Robotics and Automation Control Automotive and Robotics Lab Rawalpindi Pakistan Balochistan University of IT Engineering and Management Sciences Department of Electronic Engineering Quetta Pakistan

ISBN: (纸本)9781665464727

Terrain adaptability gives snake robots an edge over wheeled mobile robots. Snake robot's applications expansion to disaster management is due to its limbless and modular design. Replicating the navigation and locomotion of a biological snake have been in the spotlight for many researchers. In this study, a robust localization algorithm of a snake robot is developed. A sensor fusion-based algorithm using probabilistic approaches: UKF (Unscented Kalman Filter) and EKF (Extended Kalman Filter) has been proposed. Odometry is fused with one and two IMUs (Inertial Measurement Units) with both probabilistic approaches. Evaluation of results in a simulation environment showed that the fusion of two IMUs and odometry using EKF outer performs in terms of accuracy when odometry is fused with one IMU using EKF. Furthermore, the fusion of two IMUs and odometry with UKF is computationally expensive resulting in a large convergence time which is not the best suitable approach that can be utilized for the snake robot. © 2023 IEEE.

关键词： Extended Kalman filters

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Hand Gesture Classification using sEMG Signals and Ensemble Learning 3

Hand Gesture Classification using sEMG Signals and Ensemble ...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Chandran, Ranjeesh R Devaraj, D. Ashok, Saurav Shaji, Donfred Saju, Sam K Adishankara Institute of Engineering and Technology Department of Robotics and Automation Kerala Kalady India Kalasalingam Academy of Research and Education Department of Electronics and Electrical Technology Tamil Nadu Srivilliputhur India Adishankara Inst. of Eng and Tech. Department of Robotics and Automation Kerala Kalady India

ISBN: (纸本)9798350361186

Electromyographic signals offer details on a muscle activity of a person. In the case of hand movements various combinations of forearm muscles must be activated in order to carry out each gesture, which results in unique electrical patterns. On the other hand, identifying the motion being executed is made possible by the examination of these patterns of muscle activation, which are captured by EMG signals. This article presents a novel implementation on hand gesture classification utilizing Electromyography (EMG) signals recorded through a MYO Thalmic bracelet. The dataset consists of raw data collected from 36 subjects, each executing a series of static hand gestures. The classification model employed for this study is an ensemble of decision trees, achieving an impressive validation accuracy of 98.0% and a test accuracy of 98.1 %. The article outlines the dataset details, recording methodology, and provides an in-depth analysis of the model architecture, hyperparameters, and training results. © 2024 IEEE.

关键词： Decision trees

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Application of artificial neural network for prediction of fracture energy of concrete

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Asian Journal of Civil engineering 2025年第6期26卷 2629-2644页

作者： Pathak, Sudhanshu Mane, Sachin Pataskar, Smita Vemawala, Gaurang Shiyekar, Sandeep Sarnobat, Sandeep Department of Civil Engineering D Y Patil College of Engineering Akurdi Pune India Department of Civil Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat India Department of Robotics and Automation D Y Patil College of Engineering Akurdi Pune India

The analysis of fracture parameters of concrete drawing the researchers attention and getting popular day by day. Every concrete structure undergoes crack formation, initiation and propagation phase, to understand the kind and severity of crack study the fracture mechanics is very much needed. Fracture energy (G_f) is one the main characteristic amongst numerous fracture parameters. The different parameters such as water to cement (w/c) ratio, compressive strength (fc), diameter of aggregates, testing age of specimens etc. play essential role in understanding the G_f. In present work, G_f of concrete is measured by replacing cement with nano TiO₂ (NT) at 1, 2, 3, and 4% of the concrete mix, as well as fly ash (FA) and ground granulated blast furnace slag (GGBS) at 10, 20, 30, and 40%. The G_f was investigated using the size effect technique (SEM), and the notched beams were subjected to a three-point bend test. According to the experimental results, the NT4FA40 mix had the maximum G_f, while mixtures including FA out performed than GGBS mixes. Furthermore, an attempt was made to anticipate G_f using the soft computing method in light of the current necessity. The G_f is predicted using an ANN. The literature database, which includes 193 fracture tests, was gathered from earlier research in addition to the data from the current experimental investigation. Furthermore, the formula proposed by Bažant and Becq-Giraudon was utilized to make predictions based on a number of characteristics, including compressive strength, maximum aggregate size, and w/c ratio. compressive strength, maximum aggregate size, and water to cement ratio are among the characteristics that are trained, verified, and tested for ANN. The ANN model developed using literature-based data, Bažant and Becq-Giraudon equation derived data and experimental data gives promising results with R values 0.999, 0.981, 0.984 respecti

关键词： Artificial neural network Fly ash Fracture energy Ground granulated blast furnace slag Nano TiO2

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Prediction of compressive strength of concrete using multilayer perception network, generalized feedforward network, principal component analysis network, time lagged recurrent network, recurrent network

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Asian Journal of Civil engineering 2025年第1期26卷 431-450页

作者： Pathak, Sudhanshu S Mane, Sachin J Vesmawala, Gaurang R Sarnobat, Sandeep S Department of Civil Engineering D Y Patil College of Engineering Pune Akurdi India Department of Civil Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat India Department of Robotics and Automation D Y Patil College of Engineering Pune Akurdi India

The present work aimed to study the artificial neural network (ANN) and its effectiveness for prediction of compressive strength (fc). Genetic algorithm (GA) was used for optimization of five different types of ANN ne... 详细信息

The present work aimed to study the artificial neural network (ANN) and its effectiveness for prediction of compressive strength (f_c). Genetic algorithm (GA) was used for optimization of five different types of ANN networks viz. multilayer Perception network (MLP), generalized feedforward network (GFF), principal component analysis network (PCA), time lagged recurrent networks (TLRN), recurrent networks (RN). A 272 data set of f_c was obtained from the various literatures and used for training, testing and validation. Mean square error (MSE), mean absolute error (MAE) and correlation coefficient (R) used as validation criteria. Water to cement (w/c) ratio, maximum size of aggregate, curing days and cement content etc. were used as input parameter for prediction of f_c. The result reveals that MLP has more precise compared with GFF, PCA, TLRN, RN, the observed values of R is 0.97, MSE is 42.30 and MAE is 5.57, which indicates the model is best fir for prediction of f_c. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Artificial neural network Compressive strength Genetic algorithm Multilayer perception

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