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Journal of Electronic Design Technology
Journal Prestige (SJR): 0.1  Number of Followers: 8  Subscription journalISSN (Print) 2321-4228 Published by STM Journals  [67 journals]
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- A System of Smart Irrigation with Precise Pesticides and Fertilizers
Integration in Waterflow-
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Authors: Harsh Mishra, Shiksha Dwivedi, Vatsalya Shukla, Diler Singh, Gaurav Singh
Pages: 1 - 10
Abstract: The paper extensively discusses the hardware components essential for the system, including the Arduino Uno microcontroller, soil moisture sensors, water pumps, and dispensers for fertilizers and pesticides. Key IoT components, such as an IoT module (e.g., ESP8266), facilitate data transmission and remote control via a dedicated mobile application. A pivotal aspect of this research is the development of the mobile application, which empowers users to monitor soil moisture levels, control irrigation remotely, and seamlessly manage the release of fertilizers and pesticides, either manually or through automated scheduling. The paper concludes by highlighting the necessity of comprehensive testing, calibration, and documentation, to ensure the system's reliability and
robustness in various agricultural settings. Furthermore, future work may involve integrating advanced data analytics for data driven decision-making, incorporating weather forecasting to optimize irrigation schedules, and addressing scalability for larger agricultural operations. In summary, & Smart Irrigation Using IoT with Soil Moisture Sensing and Fertilizer/Pesticide Integration represents a significant step forward in precision agriculture.
By optimizing resource allocation, conserving water, and enhancing crop health, the system contributes to the sustainable future of farming practices. The project's potential to evolve and adapt to the needs of modern agriculture highlights its significance in the field of agrotechnology and environmental sustainability.
PubDate: 2024-05-22
DOI: 10.37591/joedt.v14i3.7845
Issue No: Vol. 14, No. 3 (2024)
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- Assessing the Effectiveness of Machine Learning Algorithms in Simulating
Malware Detection Processes-
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Authors: Mannu Priya, Toofan Mukherjee, Purva Agarwal
Pages: 11 - 20
Abstract: On the information system comprehends, computer virus attacks play a very important role and, by undermining regionally and globally, are considered one of the most critical threats. The traditional malware detection methods, more varied, being based on signature, are incapable of providing sufficient coverage over malicious programs in a short time. This is due to the speed of evolution and growing complexity of malware variants. This situation, in turn, requires the development of sophisticated and variant manipulating detection ways, which must be ready to attack any new development of malware. ML is an
attractive alternative and it is possible due to its ability to deduce patterns from complicated signals and because it can adjust to
the ever-growing amount of data. The paper is focused on the mathematically oriented approximation of malware detection
machine-learning system both quantitative and descriptive. The main target of this study is the performance evaluation and
behavioral assessment of the suggested system in the detection and classification of malicious processes of different types. To
accomplish this a heterogeneous dataset is used which contains both benign and malicious samples of software and they are
employed for the training and evaluation of the ML algorithms. Beyond merely understanding, these models are developed
through pattern and anomaly detection, thereby making detection precise. The performance nature of the ML element is accurately
assessed against the classic authentication (signature) –based approach and most up-to-date powerful detection tools of advanced
malware. A comparative study is inevitably needed to validate the ML approach under traditional solutions that run into problems
when a zero-day that is unfamiliar to detection or polymorphic malware is encountered.
In a nutshell, the results demonstrate that in comparison with the standard techniques, machine learning-based detection system
performs well in terms of accuracy, and detection rates. This advantage in essence illustrates that having such massive datasets is
the way forward in malware detection as it offers sleeker and more intelligent defense mechanisms. The investigations in the study
demonstrate the fundamental role of machine learning in the development of cybersecurity and proposes its inclusion in
cybersecurity strategies due to its high-level information processing abilities and flexibility making it possible to develop a smart
malware detection system capable of dealing with the sophisticated and changing threats in the internet.
PubDate: 2024-05-22
DOI: 10.37591/joedt.v14i3.7844
Issue No: Vol. 14, No. 3 (2024)
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- IoT based Healthcare Monitoring for COVID- Subvariant JN-1
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Authors: Kazi Kutubuddin Sayyad Liyakat
Pages: 21 - 27
Abstract: COVID-19 The pandemic has brought attention to how crucial healthcare surveillance is to be controlling and halting the spread of infectious diseases. The introduction of novel variations such as the JN 1 subvariant, there is an urgent need for advanced and efficient monitoring systems to keep track of the virus and its impact on individuals and communities. This is where the Internet of Things (IoT) comes into play, offering a powerful and innovative solution for healthcare monitoring in the face of the pandemic. In the case of the JN 1 subvariant, which is believed to be more transmissible than the original COVID-19 virus, early detection and isolation are crucial in containing its spread.
IoT-based healthcare monitoring can play a significant role in this regard by providing real-time data on the spread of the virus. With the help of location tracking and contact tracing, IoT can identify
potential hotspots and help authorities take necessary measures to prevent further spread.
PubDate: 2024-05-22
Issue No: Vol. 14, No. 3 (2024)
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- Electricity Theft Detection in JSS Boys Hostel
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Authors: Aaditya Pratap Malik, Punit Palial, B. P. Mishra, Udbhav Patel
Pages: 28 - 34
Abstract: This paper proposes an IoT-based system for real-time detection and prevention of electricity theft. The system integrates energy meters, optocouplers, relays, Arduino Uno, and Node MCU. It monitors energy usage discrepancies and automatically cuts power to users exceeding a predefined threshold. This approach offers real-time theft prevention, automatic disconnection, and seamless integration with existing infrastructure. By leveraging IoT, the system empowers utilities to improve efficiency, reduce losses, and safeguard the grid.
PubDate: 2024-05-22
Issue No: Vol. 14, No. 3 (2024)
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- YOLOv8 in Focus: A Review of its Application in Driver Monitoring Systems
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Authors: Sameer Awasthi, Abhishek Verma, Ritesh Kr. Singh, Vidhik .
Pages: 35 - 40
Abstract: This research presents a novel Driver Monitoring System (DMS) that utilises Convolutional Neural Networks (CNNs) to achieve remarkable results. Specifically, the YOLOv8 (You Only Look Once version 8) detection technique is used. The main goal is to increase road safety by using cutting-edge computer vision techniques to analyse driver behaviour in real-time. The YOLOv8 detection method, a cutting-edge CNN model renowned for its precision and effectiveness in object recognition, is the basis of the DMS. It focuses on using YOLOv8 to do tasks like gaze tracking, gesture detection, and facial recognition, making it possible to seamlessly monitor and interpret a range of driver behaviours. With the use of YOLOv8, the DMS can recognise and monitor important cues including gestures, eye movements, and facial expressions to evaluate the level of driver attention, weariness, and potential distractions. By doing a thorough analysis and assessing the YOLOv8-based DMS's efficacy in various driving situations. The system's capacity to reliably identify and mitigate safety concerns related to driver inattention impairment is exhibited through case studies and performance indicators. Furthermore, it discusses the ethical and regulatory ramifications of integrating the YOLOv8 detection algorithm into the DMS. Recommendations for industry standards compliance and privacy protection are addressed, with a focus on the proper application of this technology in the automobile sector. Overall, by demonstrating the effectiveness of the YOLOv8 detection algorithm in real-time behaviour analysis, this study advances driver monitoring systems. By utilising state-of-the-art CNN technology, the insights offered in this article open the door to safer and more intelligent modes of transportation.
PubDate: 2024-05-22
DOI: 10.37591/joedt.v14i3.7843
Issue No: Vol. 14, No. 3 (2024)
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- Fleet Guard: Advanced Fleet Management and Vehicle Monitoring System
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Authors: A. Meenambika, P. Karuppasamy, T. Vithyaa
Pages: 18 - 24
Abstract: FleetGuard: Advanced Fleet Management and Vehicle Monitoring is a game changing IoT solution, crafted using Flutter in the Dart language, set to revolutionize conventional fleet management practices. It seamlessly integrates software and hardware components, with a primary focus on Tire Pressure Monitoring Systems (TPMS) and GPS sensors. This innovative system offers real-time tire pressure monitoring, predictive maintenance, and driver behavior analysis, emphasizing efficiency and safety, ultimately reducing operational costs, and ensuring reliability. Developed using the efficient and robust Dart language, FleetGuard's software component provides a user-friendly interface for fleet managers and operators. This app seamlessly collects real-time data from TPMS and GPS sensors, ensuring that critical information is readily accessible without delays. The hardware component, featuring TPMS and GPS sensors, is integrated into each vehicle in the fleet, offering real-time tire pressure data and precise geolocation. Proper tire pressure is vital for safety and efficiency, and FleetGuard's TPMS and GPS sensors proactively address these concerns, preventing breakdowns and optimizing vehicle performance. FleetGuard's predictive maintenance capabilities analyze data from TPMS and GPS sensors, including tire pressure, engine diagnostics, and vehicle usage patterns. This data-driven approach enables precise maintenance scheduling, minimizing downtime and reducing costs. Additionally, FleetGuard assesses driver behavior, utilizing GPS sensor data to evaluate aspects like speeding, harsh braking, and idling. By promoting safer and more fuel-efficient driving practices, it enhances safety and lowers operational expenses. The comprehensive approach of FleetGuard, combining real-time TPMS and GPS sensor data with predictive maintenance and driver behavior analysis, results in streamlined operations, reduced downtime, prolonged tire life, and increased safety. These benefits significantly lower operational costs and offer an appealing return on investment for fleet owners. With its wide-ranging applications across industries, FleetGuard is poised to revolutionize fleet management. By reducing costs, improving efficiency, and ensuring reliability, this innovative IoT solution, with its integrated hardware sensors and Dart-powered software app, promises a safer and more cost-effective future for fleet operators.
PubDate: 2024-02-24
Issue No: Vol. 14, No. 2 (2024)
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- Data Security System for a Bank using Hybrid Algorithm
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Authors: S. Aruna Deepthi, V. Aruna, S. Jhansi, R. Leelavathi
Pages: 25 - 36
Abstract: A secure security system is critical for a secure banking system. A secure banking system is required to prevent the theft of sensitive data from banks and clients. In today's world, exchanging vital information over the internet is extremely simple and quick. The easier it is to exchange information, the easier it is for the hacker to steal our information .As a result, a strong security system is required. To maintain the customer's confidence in the system and data security, a banking system is currently required to ensure the confidentiality of the customer's data. Bank-based safety mechanisms are made secure by means of cryptographic methods. In RSA and ECC, two keys are generated: a private key and a public key.. It is the most effective data security method for defending the bank from cybercrime. In other words, both public key algorithms create the digital signature standard and its message verification. Furthermore, the Diffie Hellman method is computed to supply the user's keys in a safe manner. In terms of key exchange and mutual authentication, it is clear that ECC has more benefits and is more powerful than RSA. This paper deals with a solid security system using two different asymmetric algorithms namely, Elliptic Curve Cryptography and RSA, it will enhance data security, and consider the mutual authentication, and key exchange between two untrusted parties. Our system is protected against unwanted access by the use of the encryption methods RSA and ECC.
PubDate: 2024-03-19
DOI: 10.37591/joedt.v14i2.7732
Issue No: Vol. 14, No. 2 (2024)
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- Implementation and Verification of Dual Port RAM for High-speed
Applications-
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Authors: Deepti Kakarla, Shiva Teja K., Shravani A., Sneha M.
Pages: 36 - 41
Abstract: It is important to have an appropriate medium for transmitting data among parallel running processes in multi-processor-based applications. Multi-processor systems are used to handle complex tasks that require a lot of processing power, and they rely on parallel running processes to achieve this. However, one of the major limitations of these systems is the slow transmission of data among parallel running processes. This is due to the fact that in a single port RAM, only a single address from the memory can be accessed at a particular time during each clock pulse. This limitation can significantly reduce the efficiency of the multi-processor system. To overcome this limitation, the use of dual port RAM is recommended. Dual port RAM allows for simultaneous access of different addresses in the memory during each clock pulse, and it also supports the simultaneous access of read or write or both at a time with different addresses in the memory during each clock pulse. This means that multiple processes can access different addresses of the memory at the same time, which leads to faster and more efficient transmission of data among parallel running processes. The usage of dual port RAM is important in multi-processor-based applications as it helps to enhance the efficiency of the system by allowing for faster and more efficient transmission of data among parallel running processes.
PubDate: 2024-03-08
Issue No: Vol. 14, No. 2 (2024)
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- Text Line Segmentation for Kannada Language Using Enhanced Horizantol
Projection Profile Method-
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Authors: Shakunthala B S, Ullas H.S., Pillai C.S. C.S., M Suresh
Pages: 1 - 8
Abstract: Handwritten character image is taken as dataset for this method. Segmentation is crucial in the Human Character Recognition System for extracting text lines, words, and characters from handwritten Kannada documents. In the proposed system, segmenting text lines, word, characters are done based on enhanced horizantol projection profile approach. The algorithm will be used for finding the height and width of the entire handwritten word The horizontal projection profile approach is evaluated using photographs from a handwritten Kannada manuscript with 100 data set dimension. The system achieved an average segmentation rate of 96.38% on fully unconstrained handwritten Kannada documents.
PubDate: 2023-10-12
DOI: 10.37591/joedt.v14i2.7363
Issue No: Vol. 14, No. 2 (2023)
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- Fake Currency Detection Using Convolutional Neural Networks
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Authors: P.M.K. Prasad, D. Jahnavi, Guntu Nooka Raju, BPV Dileep, K. Lohitha
Pages: 9 - 17
Abstract: In today’s world, due to increasing technology like scanning, color printing, and duplicating, the identification of bogus notes by the human eye is almost getting impossible. Knowingly or unknowingly, due to the usage of bogus currency notes, the Indian economy is also being impacted badly. Hence, the identification of bogus currency notes is really important. This paper deals with regard to identifying whether the given sample of the currency note is real or bogus. Previously, there are many methods for the identification of bogus notes eliminating the need for manual feature extraction. Also, the results are not very accurate and hence deep neural networks can be used for the recognition of bogus currency notes. In this paper, the Convolution Neural Network technique is employed for the detection of bogus currency bills. Convolution Neural Network is an architecture that directly learns from the input data and classifies the note, if the note is found to be a bogus note, then immediately a message will be sent indicating the specified location where the bogus notes are being circulated. Hence, the problem of bogus note circulation can be reduced and also help the society not being deceived by fraudsters. The results shows that the training accuracy and validation accuracy of the proposed method are 99.6% and 99.7% respectively
PubDate: 2023-10-31
DOI: 10.37591/joedt.v14i2.7376
Issue No: Vol. 14, No. 2 (2023)
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- Coin Based Mobile Charger Using Arduino
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Authors: Shalini Sahay, Aditya Tiwari, Abhishek Kumar, Abhishek Raj
Pages: 21 - 28
Abstract: Since a few years ago, mobile phones have been fantastic tools for communication and everyday use. Therefore, maintaining a mobile phone's battery has become a more important duty. In this project, we created a working prototype for coin-operated mobile battery charging. For all mobile users who might not have access to conventional power banks while travelling or in an emergency, a coin-based mobile charging system offers an alternative solution. Shop owners, members of the public, and public spaces like bus stops and train stations can all utilise this system to charge their mobile devices. Offices, colleges, and commercial buildings can all use this technology. The system as a whole is managed by the prototype's Arduino MEGA microcontroller. The mobile phone will receive the necessary charge through this coin-based charging system, which is accessible on-demand in public spaces. The project also focuses on the system's many applications and how they might be combined to bring greater functionality, sustainability, and dependability to address people's issues with timely phone charging. Future plans for the system include using renewable energy sources to install it in remote locations that frequently face power outages.
PubDate: 2023-10-12
Issue No: Vol. 14, No. 2 (2023)
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- Voice Recognized D.C. Motor Drive
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Authors: Priyanka Dutta, Arjun Ray, Sudip Kr. Bid, Suman Pramanik
Pages: 29 - 36
Abstract: Speed controlling of a DC motor is a very important as DC motor is very useful in many industrial applications. The advancement in solid state devices has made DC motor speed regulation easier and smoother. The variation in speed can be easily obtained by the help of PWM technique where the gate pulse monitors the speed. In recent times voice automated systems are becoming very common in our day to day life. The human speech varies in many aspects such as pitch, amplitude and phonetic emphasis from person to person. This makes it difficult to implement a voice automated system but with modern microcontroller unit ATmega328P it is now easy to implement the speech recognized system and by only one command any person can start the motor driver system which rotates the motor. By using this system the direction of rotation of the motor as well as speed of the motor can also be monitored. The voice command from the Aurdino app is received by the HC-05 Bluetooth module, which then transmits it to the ATmega328P microcontroller, which then sends the signal-processed to the motor driving circuit L298N, instructing the MCU. The motor driver circuit rotates the motor accordingly.
PubDate: 2023-10-12
Issue No: Vol. 14, No. 2 (2023)
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- The Method of Electronic Voting on the Basis of Elliptic Curve
Cryptography-
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Authors: Dipayan Roy, Abhinav Shukla, Debashree Ray, Ram Krishna Akuli
Pages: 1 - 7
Abstract: To improve election efficiency, accessibility and accuracy Electronic Voting Systems which use computers to record and tabulate votes are becoming more popular to modernise voting. The Congressional Research Service states that electronic voting has various advantages over traditional paper voting. Electronic voting has made the voting process more accessible. The advancement of technology is to be regarded for the ease of being able to vote from any location. This has highly benefitted physically challenged individuals and long-distance commuters. The drawbacks of electronic voting cannot be disregarded despite the multiple advantages and increasing popularity. The three major issues are Security, Reliability and Transparency. Integrity and security concerns are raised on the instances of hacking or malfunctioning of voting systems. The integrity and security are the key factor that needs immediate addressing to maintain trust in these systems. Securing electronic voting systems ensures fair, transparent and people – driven elections.
PubDate: 2023-06-30
DOI: 10.37591/joedt.v14i1.7078
Issue No: Vol. 14, No. 1 (2023)
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- Hand-Writing Recognition Using Structural, Statistical Features
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Authors: Shweta Singh, Rimsha Mujeebur Rehman Siddiqui
Pages: 8 - 14
Abstract: One of the very crucial challenges in pattern recognition operations is handwriting recognition, often known as handwritten number recognition. The processing of bank checks, the sorting of postal mail, the entry of data into forms, etc. are all procedures involving number recognition. The ability to create an efficient algorithm that can retrieve handwritten integers submitted by drug users via a scanner, tablet, and other digital gadgets is at the core of the issue. a method for reading handwritten numbers that are based on various machine-learning techniques. The major goal of this research is to provide reliable and efficient methods for handwritten integer recognition. Numerous machines learning techniques, including the Videlicet, Multilayer Perceptron, Support Vector Machine, Naive Bayes, Bayes Net, Scikit-Learn, Random Forest, J48, and Random. Using WEKA, trees have been used to recognize integers. This design mostly uses Scikit-Learn to celebrate handwritten integers. The scikit- learn library itself provides a wide variety of datasets for model training. In this design, an integer dataset has been utilized. A portion of the data will be fed into an SVC prophetic model, and the remaining data will be used to confirm the model's performance. It is also seen how the model's delicateness changes when the rate of training and test data changes.
PubDate: 2023-09-27
Issue No: Vol. 14, No. 1 (2023)
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- Smart Programmable Energy Meter with Bill Estimation
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Authors: Shalini Sahay, Shruti Nodia, Suhana Khan, Siddharth Yadav, Vishal Bhumarkar
Pages: 15 - 20
Abstract: The idea of a rechargeable electricity energy metre, similar to how we recharge our mobile phones, is a smart one. In this project, we are developing a computerised system using a microcontroller called the 8051 and a GSM module. The project's major goal is to create an energy metre that sends SMS notifications to consumers to let them know exactly how much energy each load is consuming and how much they will be charged. An ordinary electrical energy metre has been used for this project. The front panel's visible blinking LED serves as a direct indicator of power usage. Faster LED blinking pulses are produced as more power is used. In order to calculate the real-time. The microprocessor of the 8051 family receives an interrupt signal whenever the LED blinks, and the programme therein counts the pulses as they occur and presents the reading on the LCD properly interfaced to the microcontroller, which is connected to the microcontroller.
PubDate: 2023-10-09
Issue No: Vol. 14, No. 1 (2023)
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- Automating Acquisition through SOUL 3.0
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Authors: Amit Kumar Gupta, Dinesh Kumar, Ravindra Mohan
Pages: 9 - 21
Abstract: Library automation is an integral part of the development process of any library or resource center. Traditionally this includes automation of acquisition, serialization, cataloging and circulation. But most libraries do list entries of reading material and display them via OPAC. These libraries have been equally successful in computerized issues and returns. But the real difficulty lies in the automation of acquisition activities. It is forgotten that cataloging begins with acquisition. The article describes step by step how to mechanize the acquisition process using SOUL 3.0 to strengthen library services. Mechanization involves six important steps namely vendor management, budgeting, suggestion, ordering, accession and payment. All components are depicted in detail.
PubDate: 2023-05-06
Issue No: Vol. 13, No. 3 (2023)
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- Future of Healthcare: Internet of Things
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Authors: Sherin Zafar, Kashaf Arif, Farheen Siddiqui, Sameena Naaz
Pages: 22 - 27
Abstract: The main objective of this paper, INTERNET OF THINGS (IoT) IN HEALTHCARE, is to provide an overview of the healthcare effects of IoT. Healthcare cannot be used outside this framework due to the increase in the number of IoT solutions.
The goal of this research is to outline strategies for developing worldwide connectivity between medical environments and the Internet of Things (IoT). A huge challenge is the need to merge everything (from electrical to data engineers) on a global scale. This movement is the justification for changing the way we
perceive healthcare. It also provides the applications of IoT in Healthcare by different researchers in their respective domain.
PubDate: 2023-05-06
Issue No: Vol. 13, No. 3 (2023)
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- IoT-Based Smart Automotive Parking System
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Authors: Shivanshi Mishra, Utkarsh Singh Tiwari, Akhilesh Kumar Shukla, Chandan Tiwari, Kaushal Kumar Vishwakarma, Pankaj Sharma, Dharam Pal Singh Chuhan
Pages: 28 - 34
Abstract: A billion devices and services can be connected to the Internet of Things (IoT) at any time, anywhere, and with a variety of applications. IoT has recently emerged as a technology. The topic of smart auto parking is one of the most important current research discussion topics on the IoT. Almost a million cars are on the highways of a modern urban city, but there is not enough parking. Also, the majority of modern academics advocate for cloud-based data management. The timely transmission of raw data from dispersed sensors to the parking area through the cloud and subsequent receipt of it once it has been processed may be a problem with this system, though. The Internet of Things (IoT) allows for the connection of a billion devices and services at all times, everywhere, and with a wide range of applications. The Internet of Things (IoT) is a modern technology that has emerged recently. One of the most significant areas of ongoing research in this field is the development of smart auto parking solutions. In a contemporary big city, there are almost a million cars on the roadways, but there is not enough parking. Additionally, the vast majority of contemporary academics support cloud-based data management. However, this system may have issues involving timely raw data transmission from scattered sensors to the parking lot through the cloud and subsequent receipt of it once it has been processed
PubDate: 2023-05-24
Issue No: Vol. 13, No. 3 (2023)
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- Sustainable and Smart Solutions Utilizing Feature Descriptors Analysis
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Authors: Sherin Zafar, Dr. Richa Gupta, Suhail Malik
Pages: 35 - 40
Abstract: Neighborhood highlight locators and descriptors (hereinafter extractors) play a key part within the cutting-edge computer vision for developing smart solutions. Their scope is to extricate, from any picture, a set of discriminative designs (hereinafter key points) show on a few parts of foundation and/or closer view components of the picture itself. A prerequisite of a wide run of down to earth applications (e.g., vehicle following, individual re-identification) is the plan and advancement of calculations able to identify, recognize and track the same key points inside a video grouping. Savvy cam-eras can procure pictures and recordings of a curiously situation concurring to distinctive natural (e.g., center, iris) and outward (e.g., container, tilt, zoom) parameters. These parameters can make the acknowledgment of a same key point between sequential pictures a difficult assignment when a few basic components such as scale, revolution and interpretation are show. Early disclosure frameworks play a gigantic portion in checking the exponential development of COVID-19 during pandemic period. Several helpful radiography procedures, such as chest X-rays and chest CT channels, are utilized for quick and strong area of coronavirus-induced pneumonia. Highlight location could be a prepare to identify the distinctive highlights of the picture and depicting the picture properties. Revelation and planning are a basic task in various computer vision applications, such as structure-from-motion, picture recuperation, address disclosure, and more. In this course of action, we'll be talking around adjacent high-light area and planning to analyze feature descriptors of BRIEF and ORB algorithms
PubDate: 2023-05-17
Issue No: Vol. 13, No. 3 (2023)
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