Shivesh Tiwari, Somesh Kumar, S. Tyagi, Minakshi Poonia
{"title":"Crop Recommendation using Machine Learning and Plant Disease Identification using CNN and Transfer-Learning Approach","authors":"Shivesh Tiwari, Somesh Kumar, S. Tyagi, Minakshi Poonia","doi":"10.1109/IATMSI56455.2022.10119276","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119276","url":null,"abstract":"Since there have been climate changes that have resulted in an increasing amount of unexpected rainfalls, par below temperatures, and heatwaves in the region, resulting in a significant loss of ecosystem. Machine learning has helped develop various utility tools to tackle world problems. This problem of agriculture can be solved by using various ML algorithms. This paper aims at two things - a)A crop recommendation system and b) a Plant disease identification system embedded into a single website. The datasets were publicly available over the internet. Once the features for task one are extracted, the dataset is trained on five different algorithms - logistic regression, decision tree, support vector machine(SVM), multi-layer perceptron and random forest. For the second task, three CNN architectures, VGG16, ResNet50 and EfficientNetV2, are trained, and a comparative study is done between them. For task one, random forest achieved an accuracy of 99.31%, and for the second task, EfficientNetV2 achieved an accuracy of 96.06%","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131519006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Mishra, A. Chandra, D. Choudhary, Rajkishor Kumar
{"title":"CRLH-TL Based Dual-Band Miniaturized Antenna for Microwave Communication","authors":"N. Mishra, A. Chandra, D. Choudhary, Rajkishor Kumar","doi":"10.1109/IATMSI56455.2022.10119313","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119313","url":null,"abstract":"In the past few years, miniaturized antenna design has attracted the attention of researchers because of the huge demand for compact portable microwave devices. In this article square stub, meandered lines, a reverse L-shaped resonator and a ring resonator have been arranged to form the CRLH-TL (Composite Right/Left Transmission Line) which results in a miniaturized dual-band antenna configuration. The designed antenna configuration has an overall electrical outline area of $0.31lambda_{0}times 0.09lambda_{0}$, where $lambda_{0}$ is the wavelength in free space around the ZOR (zeroth order resonance) frequency of 2.72GHz. The dual-band characteristics of the designed antenna arrangement offer 7.35% and 11.07% −10dB fractional bandwidth around the resonance frequencies of 2.72GHz and 5.51GHz respectively. Additionally, in the direction of broadside radiation this antenna configuration provides an average gain of 1.51dB and 1.94dB throughout the −10dB working bands. The proposed dual-band miniaturized antenna have average radiation efficiency of 91.78% and 95.45% throughout the −10dB operational bandwidths. The developed antenna structure can be utilized in distinct microwave communication applications, such as WLAN (5.15-5.35,5.47-5.725 GHz), and Wi-MAX (5.2-5.8 GHz).","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132812627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ashmita Roy Medha, Saroj K. Biswas, Muskan Gupta, Arpita Nath Boruah, Rahul Kumar, Vivek Verma, B. Purkayastha
{"title":"Current-best Particle Swarm Optimization","authors":"Ashmita Roy Medha, Saroj K. Biswas, Muskan Gupta, Arpita Nath Boruah, Rahul Kumar, Vivek Verma, B. Purkayastha","doi":"10.1109/IATMSI56455.2022.10119383","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119383","url":null,"abstract":"Particle Swarm Optimization (PSO) is a metaheuristic optimization method based on swarm intelligence. Due to its flexibility and ability to produce optimum performance, it is commonly used in various applications. While PSO has been used extensively to provide solutions to various complicated problems in engineering, it has also many deficiencies. Several improved PSO techniques have been proposed to compensate these deficiencies. However, there are still some scopes of improvement in its components. In this work, we have proposed an improvised PSO called Current-best Particle Swarm Optimization (CPSO) which introduces a new parameter called “cbest” that has been used in the social component of PSO to overcome the local minima issue. The suggested model, CPSO, has differentiate with the basic PSO method and the Iterative (ibest) PSO method using some optimization functions. The findings indicate that the recommended model outperforms the other models.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128352998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sugarcane Leaf Disease Classification using Transfer Learning","authors":"S. Lambor, Vithika Pungliya, Roshita Bhonsle, Atharva Purohit, Ankur Raut, Aayushi Patel","doi":"10.1109/IATMSI56455.2022.10119309","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119309","url":null,"abstract":"Agriculture is crucial to the Indian economy as it provides employment to roughly half of India's population and contributes to 17% of India's GDP. Since 1947, India has seen an enormous increase in the yield and produce of crops. Yet around 50,000 crore worth of crops are lost to pest and disease attacks every year. According to the United Nations Food and Agriculture organization, there is an approximate loss of 40% in production of crops globally due to pests and diseases. This costs the global economy more than $220 billion annually. One of the most significant cash crops grown by farmers in India is Sugarcane. Red rot and Red rust epidemics have been common for sugarcane cultivators in India. With the rise in technology and artificial intelligence, there are various methods that can provide a solution to this issue. Our paper discusses in detail about using DenseNet201, a transfer learning model, along with Support Vector Machine in the output layer to detect Red Rot and Red Rust diseases in sugarcane leaves.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128453359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and Comparative Analysis of PMSM, BLDC, SynRM, and PMAssi-SynRM Motors for Two-Wheeler Electric Vehicle Application","authors":"Kalyani Arjun Gore, R. Ugale","doi":"10.1109/IATMSI56455.2022.10119363","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119363","url":null,"abstract":"The aim of this paper is to present the design analysis and comparison between BLDC, PMSM, SynRM, and PMAssi-SynRM done under parameters of 1.5 kW,48 V for two-wheeler EV application. All four motors are used in electric vehicles. The stator and slot design of each motor are the same, but the rotor has a different structure. Design is done in ANSYS Maxwell 2D and Finite Element Analysis (FEA) is used to evaluate the performance of all the motors. Finite Element Analysis also relatable with modelling and simulation of motors. Motors performance is differentiated according to efficiency, torque characteristics, torque ripple with torque angle as well as RMS phase current and cost ratio of all the motors. In comparing the characteristics of motors best motor for two-wheeler EV application was chosen for drive implementation.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133414625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis on Affect Recognition Methods in the Wild","authors":"Karishma Raut, Sujata Kulkarni","doi":"10.1109/IATMSI56455.2022.10119419","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119419","url":null,"abstract":"Affect recognition transition from laboratory-controlled to challenging in the wild conditions is an intense area of research, with a potentially long list of important application. Audio-visual modalities are significant contributors that provide rich contextual information from real world challenging corpora. These modalities can be explored for better discrimination of real world human emotions that are complex and compound. A comprehensive literature survey is carried out to identify the most relevant big databases and the way features are extracted and fused from visual and auditory data. The main focus is on recent state of Art research work using real-world corpora and the work comparing designed framework on controlled as well as in the wild data.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116349660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kiran Dasari, Nadipudi Arjun Sainath, B. Kumar, Vimal Manohar, A. V. Hemanth, K. S. Rao
{"title":"Design and Implementation of Multi-Mode Surveillance System for Several Applications","authors":"Kiran Dasari, Nadipudi Arjun Sainath, B. Kumar, Vimal Manohar, A. V. Hemanth, K. S. Rao","doi":"10.1109/IATMSI56455.2022.10119278","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119278","url":null,"abstract":"With the rise in crimes, thefts, stealing, burglary, and offensive violations in today's technological age, it is critical that we install cameras in every conceivable public place to discover accused / criminals / fled persons. Security agents, such as cops, use public camera footage to track down the accused's movements. People are assigned to this responsibility of watching the public camera recordings. These individuals must constantly watch the detected faces and compare them to the accused faces. However, because this is a continual process, there is a high risk of manual errors when utilizing this method. The accused person's face can also be discovered using this method, but by the time the assigned person tells the nearest police station, the accused person may have left/escaped. With all of these considerations in mind, it is necessary to avoid these blunders. Manual mistake in determining the perpetrator's face and relaying the information to officials swiftly are the main problems. Installing a camera with an already supplied data collection of suspected people can help cross-check the detected faces with the uploaded data set, which is the first issue. This improves the precision of the accused's detection. The second issue is telling officials about the suspected criminal or accused in a timely manner. If the installed camera has a transmitting unit, with the receiver on the official side and the transmitter on the camera end, this will work. The information is swiftly transmitted to the authorities, and there is a good possibility that the perpetrator will be apprehended. A frequency band is fundamental for any transmission to actually occur. The frequency ranges essential for the above-mentioned transferring data are 400–500 Hz and 900–1000 Hz. The LoRa module will be used to use these bandwidths.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114433498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Complexity Comparison of Empirical Mode Decomposition and Wavelet Decomposition Methods in the Detection of Ventricular Late Potential","authors":"Daphin Lilda S, Jayaparvathy R","doi":"10.1109/IATMSI56455.2022.10119348","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119348","url":null,"abstract":"Ventricular Late Potentials (VLPs) mark the electrical instability of myocardial tissues of the heart. It has been observed in medical researches that there is a direct link between sudden cardiac death due to arrhythmia and the presence of VLPs. Early detection of CVDs can be made possible by the detection of VLPs. The wavelet-based decomposition is the most widely used method in literature however due to the multiple stages involved in the wavelet-based decomposition the computational complexity of the system is high. This paper proposes VLP detection method using the Empirical Mode Decomposition (EMD) which is simple and more efficient. The ECG signal is initially filtered and the consecutive individual beats in the ECG are averaged to obtain the Signal Averaged ECG (SAECG). The EMD is applied to the obtained SAECG which decomposes the signal into corresponding Intrinsic Mode Functions (IMFs) from which the presence of VLPs can be detected. The proposed method captures even the lowest intensity deviation present in a signal. In addition to this the Wavelet decomposition is found to be two times more complex compared to the EMD based method with respect to the number of samples given.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128210319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mangal S. Kushwah, M. Azeem, Prasanth Kumar, A. Singhal, P. Rajawat
{"title":"Hybrid Renewable Energy Based Electric Vehicle Eco-Friendly Charging Station","authors":"Mangal S. Kushwah, M. Azeem, Prasanth Kumar, A. Singhal, P. Rajawat","doi":"10.1109/IATMSI56455.2022.10119412","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119412","url":null,"abstract":"Vehicles are regarded as necessary element in daily life for various transportations. Increasing global concern over air pollution encouraged us to switching to electric vehicles. Consequently, it is crucial to have a broad infrastructure of charging stations. Hybrid renewable energy-based charging stations will help us in achieving healthy environment and less load on main grid. This paper conducts a literature review on EV charging stations based on hybrid renewable energy resources, power management systems, methodologies to attain the maximum power from renewable energy resources, mainly wind and solar energy.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134025499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Modified Perturb and Observe Maximum Power Point Tracking Technique for Handling Partial Shading","authors":"Saurabh Pal, A. Singhal, Subinoy Roy","doi":"10.1109/IATMSI56455.2022.10119319","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119319","url":null,"abstract":"To ensure that solar PV is operating at its peak efficiency, management approaches for solar PV operation are needed. Photovoltaic PV's current-voltage and power-voltage characteristics show several steps and many peaks when exposed to partial shadowing. It's possible to distinguish between LMPPs (local maximum power points) and an overall maximum power point (GMPP). Perturb and Observe is one of the high-power point techniques. This method is frequently used due to its ease of implementation and lower cost when compared to alternative methods. However, in the case of partial shading, this approach is unable to tell the difference between the local and global maximum power points. The standard perturbs and observe method's flaws will be fixed by the Modified Perturb and Observe Method, which is currently under development. Partial shadowing may now be detected using this new approach, and the position of both GMPP and LMPP can then be determined. The MATLAB/ SIMULINK-implemented boost converter and a photovoltaic system make up the test bed system. The suggested approach's functioning was verified by comparing the findings to those obtained using the more traditional “Ordinary Perturb and Observe” method. Researchers were able to use the novel approach in both natural and shady lighting situations to accurately measure the maximum power point. As well as being more precise, it is also quicker than previous approaches. So, the new technology dramatically improved efficiency and increased the amount of energy that could be harvested from solar PV arrays. In both partial shading and non-shading, the suggested model works well.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133654315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}