Volume 11 | Issue 5

 Abstract

This review article deals with the numerous cutting-edge techniques and technology that could support patients in gauging their adherence to treatment. In the extremely fragmented digital health market, which includes wearable technology, telemedicine, electronic health records, and mobile health apps, there are many small and medium-sized businesses. Among other leading companies in the digital health sector are Apple, Google, Philips, Medtronic, and Roche. By using the power of digital technology to gather, analyse, store, and exchange health data, digital health aims to increase the efficiency, accessibility, and effectiveness of healthcare. Digital health includes electronic health records (EHRs), telemedicine, mobile health applications, wearable technology, the internet of medical things, and cutting-edge digital technologies.

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Google, Philips, Telemedicine, Technology

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The emergence of new trends in trademarking in cyberspace is a response to the challenges posed by the digital age, where the growth of e-commerce, social media, and online activities have made trademarks more vulnerable to infringement and counterfeiting. As a result, it has become necessary to develop new legal frameworks and practices to protect trademarks and enforce their rights in the online environment. One of the key trends in the trademark in cyberspace is the adoption of the Uniform Domain Name Dispute Resolution Policy (UDRP), which provides a mechanism for resolving disputes related to domain names that infringe on trademark rights. The UDRP enables trademark owners to challenge the registration of domain names that are confusingly similar to their trademarks, leading to the transfer or cancellation of the domain name. Another trend is the protection of non-traditional trademarks, such as sound marks, colour marks, and scent marks, which were previously not recognized in some jurisdictions. The recognition of these non-traditional trademarks in cyberspace enables brand owners to protect their intellectual property rights more effectively in the digital environment. In addition, emerging trends in the trademark in cyberspace include the regulation of keyword advertising, which involves using a trademarked term to promote a product or service in search engine results. Artificial intelligence and big data analytics are also becoming increasingly common in monitoring and enforcing trademark rights in cyberspace. The recognition and protection of trade dress is another important trend in the trademark in cyberspace, which involves the visual appearance and packaging of a product or service. The protection of trade dress enables brand owners to differentiate their products and services from those of their competitors in the online environment. Finally, brand owners are adopting new strategies to enhance their online presence and protect their intellectual property rights, including using social media platforms and establishing their e-commerce websites. These strategies are aimed at increasing brand awareness and customer engagement while preventing trademark infringement and counterfeiting in cyberspace. In summary, the emerging trends in the trademark in cyberspace reflect the ongoing evolution of trademark law and practice in response to the challenges and opportunities presented by the digital age. These trends enable brand owners to protect their intellectual property rights more effectively in the online environment while enhancing their online presence and customer engagement.

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Trademark, Domain Name, infringement, cybersecurity, cyberspace

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Creative Commons Attribution 4.0 and The Open Definition

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The prediction of delivery modalities is critical for improving mother and fetal health outcomes. Machine learning systems have demonstrated promising accuracy in predicting birthing styles. Identifying the most important features for this prediction assignment, on the other hand, remains a challenge. This paper investigates the use of several machine learning techniques for feature selection in order to determine the best attributes that lead to reliable modes of childbirth prediction. While five different machine learning methods were investigated in order to discover the most significant algorithm for prediction based on 6157 birth data and a minimal set of characteristics. The study discovered 32 variables that might be used to predict modes of birthing and classified them into distinct groups based on their relevance.

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Machine Learning, prediction, Data Mining, Child birth.

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When equipment keeps breaking down or not working as expected, it's often because preventive maintenance was never done - only emergency maintenance. Remember that equipment is only as good as it is maintained. All mechanical equipment requires regular maintenance to keep it in top working order. Good service can mean the difference between a few mechanical failures or constant problems.The following is the guide to developing a comprehensive preventive maintenance program.All major components should be included in the maintenance schedule for proper system maintenance. These include the evaporator(s), the compressor unit, and the condenser.

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Cooling , Maintenance , Refrigeration , Compressor, etc.

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Cosmetic product is defined as any Substance or preparation Intended to be placed in contact with the Various external part of human body. [ Epidermis, hair system, nail. Lips, and external genital organ or with the teeth and mucous membrane of the Oral cavity with a view exclusively. or mainly to cleaning them. Perfuming them changing their appearance or correcting body odour and protecting them Condition keeping good them The formulated cream showed good consistency and spread ability, pH, no evidence of phase separation during study period of research. Stability parameters like visual appearance, nature, viscosity and fragrance of the formulated cream showed that there was no significant variation during the study period of research. The herbal extract containing cold cream gives the cooling and soothing effect due to slow evaporation of water present in the emulsion. The cold creams are more moisturizing as they provide an oily barrier which reduces the water loss from the stratum corneum, the outermost layer of the skin. They are water-in-oil emulsion and intended for application on skin or accessible mucous membrane to provide localized and sometimes systemic effect at the site of application

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Aloe barbadensis (gel), Bees wax, Herbal cosmetic, Cold cream cream.

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We know that every field is being advanced and changing as per the technology. IoT is a revolutionary term in advancement of technology. Soldiers are important part of army, hence for their safety purpose IoT based device can be designed called as Smart Safety Jacket. In order to collect and detect various signals for organizations, it is possible to use wearable devices like smart jackets and other accessories. If the soldier is injured the fluctuations with the heartbeat and the pulse rate will be measured and will inform the military base station through Wi-Fi module and from GPS we can locate the wounded soldiers. te sensors which coordinates with regards to the human body. It can be used to measure and observe different Smart jacket, Peltier parameters.

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Smart jacket, Peltier Plates, GPS, IOT, Safety

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Retinal fundus images are a valuable source of information for ophthalmologists to diagnose retina problems. Early detection can improve chances of cure and also prevent blindness. Retinal problems like diabetic retinopathy can be diagnosed using retinal fundus images by medical experts. In recent times, machine learning research has focused on diagnosing diseases like diabetic retinopathy by extracting features and then classifying the image. In this research our goal is to automatically classify images with retinal problems from those of the healthy ones without performing any explicit segmentation or feature extraction. Rather, we use a deep learning model to automatically classify any retinal fundus image as healthy or diseased. The architecture of the network is both simple and fast. The model has been tested on datasets which was obtained from Friedrich-Alexander University machine learning data repository. The accuracy of this model has been found to be in the range 69% to 70.1%

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Retinal Diagnosis, CNN, Deep Learning, Machine Learning, Automated Diagnosis

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Due to the presence of microorganisms in the biofilm (dental plaque) on the surface of teeth, dental caries develops as a result of the localised disintegration of the hard tissues of teeth, which is primarily caused by acids. These "cavities" are known as dental caries. Commercially accessible liquid mouthwashes with artificial active components have drawbacks such discoloration of the teeth, a higher alcohol content, taste abnormalities, xerostomia, and stability problems. Using Azadirachta indica and Curcumin, which have antimicrobial, antibacterial, antiplaque, and anti-inflammatory activity, to create the oral hygiene solid preparation (US6428770B1) in the form of herbal effervescent mouthwash tablets (CN106619318A, US8728446B2). 33 factorial design was used to carry out the optimisation study for effervescent granules. The fusion technique was used to create a total of 27 early experimental batches with different amounts of citric acid, tartaric acid, and sodium bicarbonate. Curcumin and hydroxyl propyl -cyclodextrin were combined to create a complex, which was then further investigated using scanning electron microscopy. The pre- and post-compression parameters of the produced tablets were assessed. S. mutans was the target of an in vitro antibacterial investigation using the Agar well diffusion method. The pH, effervescent time, and CO2 concentration of each experimental batch of effervescent granules were assessed. Six additional batches were chosen to create the final tablet formulation. Excellent flow qualities and post-compression parameters were revealed by the pre-compression parameter results, which were also significant.

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Dental caries, oral hygiene, effervescent mouthwash tablet, antimicrobial study, Curcumin, Azadirachta indica.

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The primary focus of this study is to examine the retellings of Indian mythology, specifically the stories of Ramayana and the teachings of Gita, and how these narratives have evolved. Despite the rigid nature of mythological works, they have undergone numerous interpretations within different cultural contexts. Ramayana itself has been recounted in around 300 versions. While we have witnessed various tales and interpretations of the epic Ramayana, Devdutt Pattanaik's book stands out as it not only retells the story but also draws attention to the multitude of oral, visual, and written retellings composed by different poets in different times and places. Each poet has attempted to unravel the puzzle of the epic uniquely. Present-day authors have also endeavored to transform traditional mythology to address contemporary issues. Although the retellings may differ in appearance, the essence of the story remains unchanged. As long as faith and culture persist in society, there will continue to be a constant surge in mythological content. The researcher has undertaken a qualitative approach to study the various factors contributing to the ongoing demand for mythological tales in the present generation. These factors include social, political, cultural, and commercial aspects. Furthermore, the researcher has analyzed the content variations within the tales of Ramayana, with a particular focus on Devdutt Pattanaik's book, "Sita," which represents a modern-day exploration and revival of mythology and 'Gita' which focuses on the teachings of 'Gita' in a modern context.

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Myth, Mythology, Contemporary Literature, Retellings, Postmodern

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A novel human corona virus, severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), was identified in China in December 2019. On January 30, 2020 the World Health Organization declared the outbreak of Public Health Emergency of International Concern due to increasing concerns over its fast spread. Vaccines represent the key weapon in fighting against COVID-19 for saving life's and ending this pandemic. Vaccines help human bodies to develop immunity againstCOVID-19. The vaccines that have been approved for emergency public use include COVAXIN, COVISHIELD, SPUTNIK-V. This vaccine provides the immunity against COVID19 by identifying it quickly and fight against it .It's common to experience some mild to moderate side effects when receiving vaccinations this is because your immune system instructs your body to react in certain ways. Some of the common side effects include pain, redness, swelling at the site of injection and tiredness, headache, muscle pain, chills, fever. Some of the rare symptoms like anaphylaxis, thrombosis with thrombocytopenia syndrome, Gillian Barre Syndrome, myocarditis and pericarditis. The aim of present study was Experimental survey on COVID-19vaccines by performing bleeding time and clotting time on vaccinated vs non vaccinated 300 volunteers (subjects).After observing the results we conclude that that the bleeding and clotting time values of vaccinated volunteers shows minimum range when compared to the non-vaccinated volunteers The two-tailed P value is less than 0.0001 by conventional criteria, this difference is considered to be extremely statistically significant. Finally the results showed that thrombosis is not a major adverse event for covid-19 vaccines.

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COVAXIN, COVISHIELD, volunteers, vaccines, bleeding time, clotting time, covid-19.

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India is gradually working toward the implementation of GST in order to eliminate the cascading effects of taxes and to provide a national marketplace for goods. According to the proposed tax reform, the State and Central Governments would each have a separate tax authority to levy taxes. on the supply of goods. This suggested rule is anticipated to contribute to enhancing tax collection and reducing leakage. This is so that the State and the Central Tax Administration can assess and monitor similar taxpayers. Before the "Goods and Services Tax" is implemented, there are several obstacles. They can be grouped under two general categories: GST administration and institution and GST design and the related structure. A broad agreement still needs to be reached regarding the design-related challenges, including the selection of neutral rates of revenue, harmonisation of the GST rate across states, harmonisation of the exempted list and excluded commodities, and threshold for the mandatory GST registration across states.

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Central and State Revenue, Businesses, GST, and VAT.

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Burnout has primarily been perceived as a workplace stress overload phenomenon, but with the passage of time and the modernisation wave at its peak presently, burnout has begun to manifest itself in the lives of the student population too. In the light of paucity of related literature within the Indian research pool, the present study was undertaken to examine the differences on the academic burnout levels among the undergraduate and postgraduate university students of Delhi NCR. The response form prepared using the Oldenburg Burnout Inventory-Student Version was circulated among the students both via online and offline mediums. A total sample of 150 students (75 undergraduates and 75 postgraduates) were drawn with the help of snowball sampling approach from various colleges of Delhi NCR. The data was analysed using Independent samples t test and the result findings indicated a statistically significant difference on the level of disengagement academic burnout dimension, whereas no significant difference was revealed on the level of exhaustion academic burnout dimension. The present findings pose pertinent implications for both public and private educational institutions toward the planning, management and prevention of burnout among their student population enrolled in various undergraduate and postgraduate programs.

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Academic Burnout, Disengagement, Exhaustion, University Students, Oldenburg burnout inventory-student version

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KEYWORDS: gestational diabetes, classification, prediction diagnosis, risk factor, pathophysiology, medical nutritional therapy, oral hypoglycemic agents

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A huge amount of images are continuously shared on Social Networks (SNs) daily and, in most cases, it is very difficult to establish the SN of the provenance of that image when it is recovered from a hard disk, an SD card or a Smartphone Memory. During an investigation it could be crucial to be able to distinguish images coming directly from a photo camera with respect to those downloaded from social network and possibly in this circumstance, determining which is the SN among a defined group. It is well known that each SN leaves peculiar traces on each content during the upload-download process; such traces can be exploited to make image classification. SN modulated noise residual can be adopted as a feature to detect the social network origin by means of a trained Convolutional Neural Network (CNN).

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Image classification, SVM, DCT, Machine Learning.

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This study aims to examine credit risk management practices in commercial banks in India and identify effective strategies and best practices for managing credit risk in the context of the Indian banking sector. The study's scope covers various aspects of credit risk management, including risk assessment, monitoring, mitigation, regulatory compliance, macroeconomic factors, financial inclusion, and customer satisfaction. The study also explores the impact of technological advancements and regulatory reforms on credit risk management practices. The study's findings can help commercial banks in India improve their credit risk management practices, promote financial inclusion, and build customer trust and loyalty. Ultimately, effective credit risk management practices can ensure the long-term stability and profitability of commercial banks, which is crucial for the overall growth and development of the Indian economy.

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Credit Risk Management, Non-Performing Assets, commercial banks, India, risk assessment, risk monitoring, risk mitigation

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Today, the problem of early detection of depression is one of the most important problems in psychology. Mental fitness issues are one of the most common fitness problems worldwide, with over 300 million people currently feeling depressed due to their desperation. Due to the large amount of personal data present on social networking platforms, researchers are increasingly looking to device usage to determine if this content can be used to uncover mental health issues in users. doing. Depression is a disease that is an anomaly in our society and continues to be a topic of constant interest to researchers around the world. Despite the extensive analysis of data on people's moods, including depression, anxiety, and stress, collected by popular computing devices such as smartphones, predicting depressed mood remains an open question. question. To address this issue, a comprehensive assessment of social networks is performed. In this article, we proposed a hopelessness assessment and suicidal ideation detection system for predicting suicidal behavior that corroborates levels of hopelessness. This gift explores the ambition of maximizing our knowledge of strategies for identifying posts by people with high likelihood of depression on social media. To this end, we developed and researched a classifier to distinguish between people who are depressed and who are underutilizing the skills they have acquired in sports in their posts. Typical device algorithms are used to teach and categorize pain into different levels on a scale of 0-100%. Additionally, statistics are collected in the form of posts and categorized according to whether the person tweeting is in pain. Predictive techniques are being developed for early detection of depression and other mental illnesses using machine learning algorithms. A major contribution of this study was to explore communities of skills and the impact of those skills on perceptions of depressive conditions. This study explores plans to develop an in-depth knowledge analysis to classify depressed consumers through multiple knowledge instances, ranging from personal labels to postal labels. By combining all the possibilities of postal label categories, you can create a temporary post profile and use it to categorize your troubled customers. This paper suggests that there is a marked difference in posting style between desperate and non-desperate customers, represented by the mixed probabilities of post-label categories. This study uses a data collection device to process scrap statistics collected from social media user posts. A natural language processing (NL P) classified use of the BERT rule set for detecting depression in a more practical and green way.

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Machine Learning, NLP, BERT Algorithm, Depression, Classification, Social Media Post.

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 Abstract

Introduction:Pneumothorax is the most common respiratory condition seen. It can occur in conjugation with other diseases or can be traumatic. Intercostal drainage is the standard form of treatment for pneumothorax that basically removes the excess air filled in the pleural space. This ICD causes a decrease in mobility of the chest wall and chest expansion, dyspnea, and Pain. Physiotherapyadded with early mobilization and when started initially in the post-ICD period is helpful to get better outcomes and decrease hospital stay length. For this,Chest physiotherapy plays a main role in enhancing lung expansion and regaining the chest wall and lung mobility after a thoracic surgical procedure.TENS is a readily used modality in post-surgical pain complaints. Aim:The aim of this study was to find the additional Effects of TENS along with conventional physiotherapy on dyspnea and chest mobility inpost-intercostal chest drainage (ICD) patient at the end of 10 days. Design: Single subject case study. Method and procedure:Single subject with complaint of pain, dyspnea, and reduced chest expansion post-ICD tube removal was selectedfor the study. A formal informed consent was taken from the patient and all the outcome measures were noted on day 1. Conventional TENS was applied around the site of the incision and conventional physiotherapy such as ACBT, pursed lip breathing (PLB), diaphragmatic breathing, and segmental breathing were also given. After 10 days of protocol, post-readings were noted. Then pre- and post-outcome results were compared to evaluate the significance of the study. Result:After the intervention, there was a significant improvement in chest expansion and there was a substantial decrease in NPRS and mMRC dyspnea scale scoring. Conclusion:Based on the results, it can be concluded that conventional TENS can be used in conjunction with chest physiotherapy for post-ICD removal subjects as it significantly improves chest expansion and decreases pain and dyspnea scores.

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TENS, Pneumothorax, Intercostal Drainage, Physiotherapy

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This paper deals with the congestion management approach under Combined Economic Emission Dispatch (CEED) in a deregulated electricity market using Artificial Bee Colony (ABC) algorithm. Transmission congestion is a condition that occurs when excess power flows over a line exceeding the power flow limit of the line in a deregulated electricity market. As the real power dispatch has a major role in relieving the transmission congestion at low cost, this paper deals with rescheduling of real power generation to manage congestion. Contributions made in this paper are of two stages. Transmission Congestion Distribution Factors for the congested lines is evaluated in the first stage for optimum selection of participating generators. An algorithm based on ABC is used in the second stage for obtaining minimum values of generator power outputs after rescheduling under CEED. The price penalty factor method is used to convert multi-objective CEED problem into single objective function. Test results on IEEE 30-bus six generatorsystems indicate the effectiveness of ABC approach in optimizing rescheduling cost and CEED.

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Congestion management, Deregulated Electricity market, Transmission Congestion Distribution Factor, Artificial Bee Colony, Combined Economic Emission Dispatch.

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Access to healthcare and medical advice plays a crucial role in maintaining a good quality of life. Unfortunately, obtaining timely advice from healthcare professionals can be challenging. To address this issue, we propose the development of an AI medical chatbot capable of diagnosing diseases and providing basic information about them prior to consulting a doctor. This chatbot aims to reduce medical costs and enhance access to medical knowledge by leveraging a computer program that interacts with users using natural language processing techniques. The chatbot utilizes a database to store relevant information, employing keyword identification to determine user queries and provide accurate responses. Furthermore, sentence ranking and similarity calculations, incorporating n-grams, TF IDF, and cosine similarity, enable the chatbot to assign scores to sentences within a given input sentence, facilitating the retrieval of more relevant and similar sentences for a specific query. Additionally, an expert program is integrated as a third-party solution to handle questions that are not understood or not present in the database. Through the proposed AI medical chatbot, we anticipate improved access to healthcare information, empowering individuals with preliminary knowledge before seeking professional medical assistance. This research contributes to the advancement of healthcare technologies and addresses the challenges associated with obtaining prompt medical advice.

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Chatbot, Healthcare, Virtual assistance, n-gram, TF-IDF, Disease information, Cosine similarity, Expert program, medical costs, medical knowledge.

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Creative Commons Attribution 4.0 and The Open Definition

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There has been a growing interest in smart bags for women's safety in recent years. These packs consolidate innovation and different elements to assist ladies with having a solid sense of safety when out openly spaces. The utilization of such packs is a significant stage towards addressing orientation based brutality and enabling ladies to assume command over their own security. Even though these bags can be useful in some situations, it's important to keep in mind that they won't solve the problem of violence against women. This article will discuss the advantages and drawbacks of smart bags for women's safety, as well as what to look for in a bag for personal use. In many parts of the world, gender-based violence is a problem that affects everyone. Women are frequently the primary victims of this kind of violence, and they may feel especially vulnerable when they travel alone or to unfamiliar locations. Because of this test, various organizations and architects have created shrewd packs that integrate security highlights, for example, GPS following, crisis alerts, and self-protection devices. GPS tracking is one of the smart bag's most crucial safety features for women. With this component, ladies can follow the area of their pack continuously, which can be particularly useful assuming that the sack is lost or taken. Additionally, some bags include an emergency alarm that can be activateuser. These highlights can provide ladies with a more prominent feeling of certainty and control when out openly spaces .It's important to remember that smart bags for women's safety can be useful, but they can't take the place of more comprehensive efforts to stop gender- based violence. We must continue to address the root causes of violence and harassment in order to create safe communities .There are a number of factors to consider when selecting a smart bag for personal use, including its cost, ease of use, and safety features' effectiveness. In the end, it is up to the individual to decide whether or not to use a smart bag for women's safety. People should choose what works best for them based on their particular circumstances and requirements.

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GSM , GPS, Arduino Uno, MCU, Voice detector sensor

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