International Journal of Engineering and Manufacturing @ijem
Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 597
Angle measurement on a flat surface using high frequency ultrasonic pulse
Статья научная
Ultrasonic waves are most commonly used to measure the presence of an object and its distance from the source using time of flight concept. These are pulses of sound waves that have frequency range higher than the human hearing range. In this paper, we will discuss the measurement of the tilt angle of a robot with respect to a flat base using ultrasonic waves and time of flight concept [2]. An Arduino platform was used with Atmel328P as the processing microcontroller chipset which will then compute the angle of tilt using the distance calculated from an ultrasonic sound transmitter and a receiver using coordinate geometry and trigonometric functions. A combination of gyroscope and accelerometer is also used to find the true tilt angle of the apparatus and then it is compared with the angle readings obtained from the ultrasonic sensor system. A high response time and low delay is necessary for instantaneous angle measurement. Hence, gyroscope-based angles have been used as a reference to adjust filter parameters to decrease error and noise at every iteration.
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Animation of magnetically levitated shoes and its optical flow with computer vision
Статья научная
The article presents a concept of computer-aided design and three-dimensional (3D) computer animation of a newly proposed magnetically levitation based shoes where the users can move in the air. The aerial movement would be in the direction of a magnetic track which is laid down below the trajectory and the users have to wear the maglev shoes. They can move from ground floor to upper floors as in the case of an elevator. The users have been provided adequate control over the speed of movement and they can stop and run the system by themselves at any instant of time by self-controlling of the motion generated by them. The maglev shoes are proposed to be built with superconducting materials to levitate above the magnetic tracks. Computer vision features are efficiently utilized to detect various features of the animated image frame of maglev shoes and the motion study of the proposed system. Statistical methods with existing functions are used to analyze various features like speed, angles and finding the optical flow in both horizontal and vertical direction of maglev shoe wearers.
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Anomaly Detection in Crowd Video Using Different Versions of YOLOv8
Статья научная
This paper focuses on real-time anomaly detection in surveillance video using YOLOv8, the latest in the YOLO object detection series, integrated with spatio-temporal analysis. The system aims to detect abnormal behavior in crowded environments by combining spatial object detection with temporal activity analysis. YOLOv8 is used to detect and track individuals in video frames, while a 3D Convolutional Neural Network (3D CNN) processes sequences of frames to identify behavioral anomalies based on movement patterns. Three variants of YOLOv8—Nano (n), Small (s), and Medium (m)—are evaluated for performance trade-offs in accuracy, processing speed (FPS), and latency. Results show YOLOv8n offers the best real-time performance, while YOLOv8m provides higher accuracy at the cost of increased latency. The system uses the UCF-Crime dataset for training and testing, and metrics such as accuracy, FPS, and latency are used for evaluation. The modular pipeline supports scalability and real-time deployment, with visual outputs aiding interpretation. By integrating object detection with spatio-temporal modelling, the system effectively identifies anomalies such as loitering or sudden movements. Future work includes refining detection accuracy using labelled anomalies and exploring advanced models like Transformers for improved temporal understanding. The significance of this research lies in its ability to combine lightweight real-time object detection with effective temporal behavior modeling within a scalable and modular architecture. The proposed framework contributes to the advancement of intelligent surveillance systems by improving anomaly detection reliability while maintaining computational efficiency suitable for deployment in smart cities, public safety monitoring, and edge-based surveillance applications.
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Any touch: design and implementation of a touch interface for bluetooth enabled personal devices
Статья научная
Human Computer Interactions has been a matter of great consideration for engineers, researchers, designers and industrial experts from decades. Every device, be it a smart phone, personal computer, ATM machines, etc. comes with a user interface for a layman to understand and to use the device. With the advancing technology, different modes of user interface are proposed. The most common of all is a touch interface. Most of the interactive devices now come with a touch interface. This paper presents an approach to provide a similar external touch interface for laptops and computers that further can modify for much smaller devices such as mobile phones.
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Application of AC Algorithm Based on RS in Stock Index Prediction
Статья научная
The AC Algorithm may easily get a lower pattern similarity when performing the AC under the situation of encountering multi-dimensional data, so this will affect the selection of similar patterns. Combining the Rough Set theory, the author makes the data dimension reduction processing. The experiment shows that the AC algorithm based on RS is practical and its performance efficiency and prediction accuracy are much higher than the AC algorithm.
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Статья научная
Soil mechanics problems deal with various types of soil that exhibit erratic behaviour in the real world, one such soil being the expansive soil where it takes a lot of laboratory test procedures to ascertain the physical properties of this soil. Modeling the behaviour of the expansive soil is complex and sometimes beyond the aptitude of most traditional procedures of physically-based engineering approaches. Artificial neural networks (ANN) are the ones used for predicting the complex nature of the soil since it has shown superior predictive potential as compared to the conventional approaches. This review aims to deliver and discuss the numerous applications of artificial neural network technique accomplished by various researchers in the field of geotechnical engineering to predict several properties of the expansive soil such as free swell index, unconfined compressive strength, shear strength of the soil, swelling pressure and swell percent, compaction characteristics, and plasticity index. This paper will assist practising engineers in determining the best modelling approaches and formulating the necessary data for using the ANN technique to solve soil mechanics problems.
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Application of Fuzzy Logic in Automated Lighting System in a University: A Case Study
Статья научная
Applications based on Fuzzy logic use mathematical reasoning to find the solution to the minutest possible fuzzy set that can range anywhere between 0 and 1. In this study, the practical implementation of a fuzzy logic controller for automated lighting was presented as a real case of an Indian university to detect the occupancy in the classroom and maintain the luminance level by sensing the daylight in the room. The result of the experiment indicates that the fuzzy logic control method could reduce wasted hours of lighting in unoccupied classrooms.
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Статья научная
The particle swarm optimization (PSO) algorithm is a stochastic global optimization technique based on swarm intelligence. It possesses advantages such as being a simple principle, few parameters and easy to be realized. In this paper, an optimization model is established to solve the difficulty in selecting parameters and improve the simulation accuracy of the biodegradable medical polymer degradation model. When modeling, the particle swarm optimization (PSO) algorithm is proposed to solve the model and calculate undetermined parameters of the biodegradable medical polymer degradation equations. A comparative analysis of the calculation results is progressed. It shows that parameters determined by optimization model make the simulation results of degradation model more close to the experiment results. Using this method to solve the model is more accurate and efficiency than determining parameters artificially. It also shows that the particle swarm optimization algorithm used to optimize parameters have practical significance and application value.
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Application of Python in Evaluating the Volume of 3D Shapes Using Monte Carlo Simulation
Статья научная
Volume estimation of three-dimensional (3D) objects is fundamental in various scientific and engineering fields. While analytical expressions exist for the simple geometric shapes, they become impractical for complex or irregular structures. Monte Carlo simulation is a statistical method which is based on the random sampling, which offers an efficient numerical alternative. This research explores the application of Monte Carlo integration method for the estimation of the volumes of three different 3D objects viz. sphere, cylinder, and cone. The paper elaborates on the mathematical background of the simulation by presenting detailed Python implementations, and analyzes the accuracy, convergence rates, and computational efficiency of the method. The study concludes that the simulation, despite their probabilistic nature, provide an effective and scalable technique for volume estimation, particularly for the shapes without closed-form volume expressions.
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Applying Motion Capture in Computer Animation Education
Статья научная
This paper introduces the motion capture technology and its use in computer animation education. Motion capture is a powerful aid in the course of computer animation and a supplement to the traditional key-frame animation. We use professional cameras to record the motion of the actor and then manipulate the data in software to eliminate some occlusion and confusion errors. For data that is still not satisfying, using data filter to smooth the motion to cut some awry frames. Then we import the captured data into Motionbuilder to adjust the motion and preview the real-time animation. At last in Maya we combine the motion data and character model, let the character perform the captured data and add the scene model and music to export the whole animation. In the course of computer animation, we use this method to design the animation of military boxing, basketball playing and folk dancing.
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Artifacts Removal of EEG Signals By the Application of ICA and Double Density DWT Algorithm
Статья научная
Independent Component Analysis is used for the automation and detection of brain artifacts. The Independent Component Analysis (ICA) here is used for the segmentation of artifact peaks in the signal. Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result. We have extended our search and applied the Double Density Algorithm for the multi-level transfer. The results obtained were analyzed from the data set of EEG signals taken with a outsource reference. Since the method is parameter free implementations in clinical settings are imaginable.
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Статья научная
This study proposes an optimized Multi-Histogram Equalization (OMHE) technique for contrast enhancement while preserving the brightness of an input image. The objective of this study is to improve the visual interpretability or perception of information among color images. In this technique, input image histogram is partitioned into multiple sub-histograms and then classical histogram equalization process is applied to each one. Values of t threshold points for dividing the image histogram into t+1 sub-histograms are optimized using Artificial Bee Colony, a swarm intelligence-based optimization algorithm. A new fitness function for evaluating the contrast of enhanced image is proposed here that will guide the Artificial Bee colony algorithm into finding the optimal threshold values. AMBE (Absolute Mean Brightness Error), PSNR (Peak signal to noise ratio), SSIM (Structural Similarity Index) and Entropy are computed for quantitative analysis of the performance of the proposed method with existing methods. Comparisons show that proposed method performs better than other present approaches by enhancing the contrast well while preserving the brightness of the input image.
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Artificial neural networks based approach for predicting LVDT output characteristics
Статья научная
This paper presents a novel approach for training and output prediction of data of a Linear variable differential transformer (LVDT). LVDT is a commonly used device used in laboratories for measuring linear displacements in specific situations. This article considers application of Artificial Neural Networks (ANNs) for learning and output estimation of LVDT. Real-time experiments were conducted and results were collected for training of ANNs. The Regression results and outputs verified the learning and prediction capability of ANNs.
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Статья научная
To improve surveillance, the proposed patrolling security system employs autonomous mobile robots outfitted with low-cost night vision cameras. Regular patrols, which are essential for discouraging criminal behavior, are typically conducted by security or law enforcement officers with the use of pricey CCTV equipment. The goal of using autonomous robots is to save expenses while enhancing the quality of patrols in particular regions. Using a night vision camera, the late-night guarding robot detects human movement within its assigned zone while following a random path. Its obstacle-detecting sensors help to prevent crashes and guarantee secure navigation. The robot records incidences, takes pictures with its mounted camera, and carefully scans regions for probable incursions. It then sends the data to the user as quickly as it can. This project's primary goal is to draw attention to suspicious activity in hidden areas.
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Статья научная
The determination of strength properties i.e compressive strength, flexural strength and splitting tensile strength is essential to estimate the load at which the concrete members may crack especially in aggressive environment. The paper reports an experimental investigation on deterioration of used engine oil (UEO) soaked flyash concrete with respect to its strength properties and effective automation of classification of data sets returned by the SEM test on the same set of samples. In the former part, concrete cube ,beam and cylinder specimens with fly ash admixture as partial replacement of cement by 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35% and 40% were subjected to water curing and then to UEO soaking. Gradual decrease in the strength properties of concrete specimens with respect to time was observed. An attempt has been made to study the permeation properties like soroptivity with the addition of fly ash in concrete. The SEM analysis of test results was in good agreement to this. An attempt was made to automate this analysis phase using correlation coefficient and Support Vector Machines (SVM). It was found that the latter achieved better results in terms of performance.
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Automated Roof Top Plant Growth Monitoring System in Urban Areas
Статья научная
Innovation is progressing at a quick pace so it is required to utilize it in an each fields to have the coveted and appropriate yield. Present day's robots are winding up plainly more well-known and are progressively depend upon embrace schedule, regularly dull errands which are costly to do utilizing generously compensated labor. Because of the expanded populace and urbanization less space found for cultivating particularly in urban regions. There is a need of self-creating of slightest individual prerequisites. To fulfill ordinary demand in green vegetables and love towards their indoor and outside plants can be expert through urban rooftop gardening. This paper clarifies essential assignments of checking and detailing the development status of plants in urban rooftop gardening. We execute the customary checking of plants development. Height of the plant is one of the parameter to decide the growth of the plant. The tallness of the plant is more than the predetermined typical height in the program; robot shows that as overgrown, if there is no development discovered robot will show that as vacant slot. For identifying the development of the plant we utilize Sharp GP2D12 sensor, three white line sensors of ATMEGA 2560 FIREBIRD V to take after the arena of cultivation slots.
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Automated Wall Painting Robot for Mixing Colors based on Mobile Application
Статья научная
The final stage, which is the building paint or the adopted design, is where most real estate developers and constructors struggle. Where extensive painting is required, which takes a lot of time, effort, and accuracy from the firm doing the work. Additionally, it might be challenging to decide on the precise color grades for the design and calculate the right amount of paint to use for the job. Where these activities are extremely expensive, and the complex implementation is accompanied by worries and skepticism. These are the motivations behind the development of painting machines that blend colors. Artificial intelligence is used in the machine's design to make it efficient and quick at what it does. High accuracy is needed when selecting the proper colors, and this machine is distinguished by its ability to select the proper color tone. The color sensor (TCS34725 RGB) determines the relevance and accuracy of the desired color by comparison with the system database with the assistance of the light sensor (STM32), which measures the degree of illumination of the chosen place. By combining basic colors, this technique saves the customer the hassle of looking at specialized stores for the level of color they require. By giving the system the codes assigned to each color, it may also blend colors. The system also has the feature of controlling the machine remotely via smart phone application by enabling bluetooth and wifi features.
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Automatic IoT based plant monitoring and watering system using Raspberry Pi
Статья научная
The main objective of this proposed work is to develop an Embedded System for plant monitoring and watering system using Internet of Things, Raspberry Pi as Processor, and sensors for sensing environmental conditions. In this work, IoT concept is introduced to connect devices through Internet and facilitate information access by the users. The system can obtain accurate perception of Environmental information in agriculture field and then transmit the same to users. The system monitors different parameters like Temperature, Humidity, Soil Moisture and Intensity of light. IR sensor is fixed to check any external object entry into the field, in case of intruder detection buzzer will turn on for few seconds. The Motor fixed in the field operates both manually and automatically depending upon Moisture sensor results in soil. Motor automatically switches between on and off stage of pumping action. Results are observed either in web app and monitor.
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Automatic System Recognition of License Plates using Neural Networks
Статья научная
The urgency to increase the efficiency of recognition of car number plates on images with a complex background need the development of methods, algorithms and programs to ensure high efficiency, To solve the task the author has used the methods of the artificial Intelligence, identification and pattern recognition in images, theory of artificial neural networks, convolution neural networks, evolutionary algorithms, mathematical modeling and models characters were then statistics by using feed forward back propagated multi layered perception neural networks.. The proposed this work is to show a system that solves the practical problem of car identification for real scenes. All steps of the process, from image acquisition to optical character recognition are considered to achieve an automatic identification of plate.
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Automatic plant Irrigation Control System Using Arduino and GSM Module
Статья научная
The evolving information technology abridges the hardship in the daily life of consumers all over the world, hence the application of this knowledge in the irrigation field is necessary nowadays. The exponential growth of demand in food is due to the ever-evolving population of the world, thus it becomes necessary to expand the present area of cultivation. Considering the present situation of weather change due to global warming as a result of industrial activities, farming via irrigation is the reliable process of food production. Water remains the only source for survival for crop production, thus optimal management and proper use of water become pertinent with the ever-increasing land for irrigation. Arduino based automatic plant irrigation control system; provides a simple approach to automated irrigation. This work makes use of the GSM module for the notification of the user about the situation in the farm, this project aims to design and implement an automatic plant irrigation control system using Arduino and GSM module. In this proposed system, there are two main parts hardware and software units. Mechanical units which are the hardware unit comprises of instrumentation systems and watering irrigation systems. The equipment system is based on microcontroller, flow meter, moisture sensor, LCD, and GSM module. The software part comprises of C++ code, this is to enable the linkage between various modules. The main control of this system is the microcontroller unit that serves as the brain for coordinating control for various modules of the system, it synchronizes and operates the watering system and notifies the user about the condition of the field and watering section via GSM module. Implementation of this project will significantly help in a water-saving of about 30 – 50% as compared to the conventional watering system like the sprinkler, improve growth and discourage weeds because water will only be served to the needed area, simple method and timer-based system for automatic watering can be incorporated for efficiency.
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