MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

Consider a person with full mental capacity and an active lifestyle who is now unable to communicate or connect with the world around them due to a serious motor impairment to the point of being locked-in to their body. Assume the person is unable to notify their caregiver when they are uncomfortable or in distress. Caregivers dealing with locked-in patients must currently rely on their instincts, troubleshooting skills, and standard operating procedures to offer the best care possible. And with these safeguards in place, patients continue to suffer from needless rashes, illnesses, and deaths that should have been avoided. Modern technologies could significantly change this outcome and are being under-utilized in such healthcare environments.

School of Computer Engineering & Technology

Engineering and Technology

Patient Behavioral Analysis with Smart Healthcare and IoT

Humans in which humans may control machines with their brains. Understanding current new technologies, such as Brain-Computer Interface, can help to ensure that successful solutions become a part of daily life. The latest advancement in Human-Computer Interaction is the Brain-Computer Interface (BCI) (HCI). BCI allows for either directly generated commands between external software applications and the human brain (active BCI) or communication between individuals and machines, resulting in a seamless and advantageous user experience (passive BCI). With over 100 billion nerve cells, the human brain is responsible for numerous sophisticated executive activities such as reasoning, task planning, and thinking processing. As a result, the brain generates a significant amount of neural activity, which can be used as input in a variety of BCI applications. This chapter provides a thorough examination of the current state-of-the-art of a complete BCI system. First, a brief introduction of BCI systems based on electroencephalograms (EEGs) is provided. Second, a large variety of well-known BCI applications are examined in terms of electrophysiological control signals, feature extraction, classification techniques, and performance evaluation metrics. Finally, the problems with modern BCI systems are explored, and potential remedies to the problems are suggested.

EFFLATOUNIA - Multidisciplinary Journal

Brain Computer Interfacing for Detection of Stress Level through EEG Signals

COVID-19 (SARS CoV-2) has already claimed more than 3.3 million lives worldwide. Many patients of COVID-19 are suffering from Mucormycosis. The use of technology helps to improve accuracy, saves time and energy to make precise decisions that will save lives of patients. Day by day new problems arise and IoT, Cloud Computing, Big Data, Machine Learning, Artificial Intelligence, etc. have been helping to analyze new problems more quickly and supports better design strategies. The sensor-based devices feeds the data to process, analyze and provide a solution. Machine Learning Algorithms are used to make precise decisions with the help of existing data repository with similar kinds of symptoms in patients, history of allergies, surgeries, and treatment. This proposed model will help to guide medical professionals to provide solutions to the problems arising in the treatment of COVID-19 and post-treatment diseases like Mucormycosis (also known as Zygomycosis).

i-manager’s Journal on Software Engineering,

SMART HEALTHCARE USING INTERNET OF THINGS (IoT) FOR REMOTE DIAGNOSIS OF COVID-19 PATIENTS

Every year, a large number of persons are killed in highway departure crashes due by driver inattention. Because safety is the primary goal of these systems, lane detecting systems can help prevent accidents. Such systems are designed to detect lane markings and alert the driver if the vehicle is drifting out of its lane. Several lane identification systems have been proposed and effectively proven in recent years. The hybrid median filter was used in this study to provide a noble strategy for lane detecting. Lane detection is used in a variety of intelligent vehicle applications, including lane trip recognition and warning boards, intelligent journey control, and autonomous driving. The majority of previous research has ignored the use of image filtering algorithms.

INTERNATIONAL JOURNAL OF ADVANCE RESEARCH, IDEAS AND INNOVATIONS IN TECHNOLOGY

Survey on lane detection techniques

When it comes to launching a new venture or developing an existing one, location is one of the most critical aspects to remember. The right location is important not only for attracting more consumers and increasing profits, but it can also decide whether a company can prosper based on factors such as the existence of competition. We plan to summarize current systems in this survey paper and, based on the research gaps, suggest a new recommendation framework that separates users into: A] Starting New Venture for an Established Business: Using the K-means clustering algorithm to propose locations, analyze the data of market locations with the type of sector where there is a high industry level and average customer ranking. B] Starting a New Business: Using Correlation Analysis between various business sectors to suggest locations using a ranking algorithm, find the best place to start a business where there is strong industry demand and little or very little supply.

An International Scholarly Open Access Journal, Peer-reviewed, Refereed Journal

LOCATION BASED RECOMMENDATION SYSTEM FOR BUSINESS EXPANSION

International Journal of Advanced Science and Technology

Optimum analysis of brain activities by using classification and learning techniques

The main challenge of wireless sensor network is its lifetime. In this type of network, single static sink node is present; a sensor device node requires more energy for estimating information packet specifically those that are available in the area of the sink node. Such nodes separate the energy so fast due to the numerous tone traffic patterns and at the end they die. This uneven event is named as hotspot issue which gets more real as the numbers of sensor nodes increase. Generally, replacement of such energy sources is not a feasible and cost-effective solution. For this problem, there is one solution regarding to distance. If the distance among sensor and sink node is minimized, the energy consumption will be effectively reduced. This paper presents the solution for enhancing network lifetime with energy saving of sensor nodes. Here, we also discuss on the limitations and advantages of previous methods. The sensors nodes consume more battery power which is at minimum distance from sink node. Therefore, energy of sensor nodes in network will quickly consume their energy. So that, the lifetime of a sensor nodes will be produced. To overcome this drawback of this system, we propose alternate shortest path technique. To enhance the efficiency of energy along with network lifespan, this approach is used. Furthermore, we developed a novel technique known as Energy Aware Sink Relocation (EASR) for remote base station in WSN if the energy of alternate path is going to die. This system exploits information recognized with the remaining energy of sensor nodes battery for increasing the range of transmission of sensor node and relocation technique for the sink node in network. Some calculated numerical and theoretical calculations are given to demonstrate that the EASR strategy is used to increase the network energy of the remote system essentially. Our system proposes secure data sending using ECC algorithm and increases more network lifetime.

Intelligent Computing and Information and Communication

<a href="https://scholar.google.com/citations?view_op=view_citation&amp;hl=en&amp;user=fpZygLkAAAAJ&amp;citation_for_view=fpZygLkAAAAJ:UeHWp8X0CEIC">Routing with Secure Alternate Path Selection for Limiting the Sink Relocation and Enhanced Network Lifetime</a>

To perform some operation there is a need of some amount of energy over the node is same to the sending the single bit of data in the network. Data transportation reduces the network lifetime when sending data in sensor network. So the need to reduce the energy consumption for improving the network lifetime. As cluster head is aggregator node of the cluster it can take part in communication many times while communication is going on in the cluster members. That's the reason that the energy utilization of the cluster head is high as compared with the cluster members present in the cluster. The present system has a way to choose the cluster head unplanned due to its high level of energy consumption. To answer this problem we introduced a system represents a technique in that effective cluster head is chosen based on the distance from the base station as well as remaining energy. After selecting the cluster head, it makes use of minor amount of energy of sensor network as well as helps to improve the lifetime of the network of sensor network. Aggregation of the data received from the cluster members is duty of cluster head in the cluster. Verification of data is done by the cluster head prior to the data aggregation if data received is not valid then received data is discarded. Only verified data is taken for aggregation at cluster head. Encryption is done by making use of homomorphic encryption method as well as encrypted information send to the cluster head and information decryption is performed by base station (BS) for giving end to end security. An ID based signature technique is developed for hop by hop authentication. In this paper, we present the method for recovering the data which is lost due to the buffer overflow. In given system cache memory is provided by the cluster head for recovery of data loss. At last test results shows depending on parameter like time as well as energy consumption on Jung simulator that system presented is good compared to the avail...

H-WSN with maximized QoS using secure data aggregation

As we know Web caching and pre-fetching is a ubiquitous technique that can increase the speed of Web loading process. Because of mobile context has limited resources like speed and memory, a better technique for Web loading process is needed. In this paper we are going to study a new a hybrid technique based on combination of ANN and Particle Swarm Optimization (PSO) for classification Web object either to cache or not and generate rules from log data by using Rough Set technique on proxy server (Rough Neuro-PSO). This technique proves to be faster in searching or accessing process in mobile applications. This method is by using XML file for prefetching which is saved into mobile memory. Prefetching that used xml file is much faster to be searched or accessed. Where in web caching side enhance the speed by using Rough Neuro-PSO in order to choose the log. At the end study the new framework which up the access of the web page in mobile environment.&nbsp;

<a href="https://scholar.google.com/citations?view_op=view_citation&amp;hl=en&amp;user=fpZygLkAAAAJ&amp;citation_for_view=fpZygLkAAAAJ:IjCSPb-OGe4C">Web Caching and XML Prefetching for Accessing Social Sites from Mobile Environment</a>