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Driver drowsiness is one of the major causes of road accidents which leads to fatal and non-fatal injuries, sudden deaths, and substantial monetary losses. Due to advancements in technologies like Artificial Intelligence (AI), various approaches have been carried out to detect driver drowsiness at the early stage. The existing measures comprises certain issues like intrusiveness, variation in results, and tested in simulated environment only. A hybrid solution is the need for early detection of drowsiness of driver by amalgamation of multiple effective measures. Many researchers have concluded that developing a driver drowsiness detection system by using hybrid measures would be more efficient and highly recommended. The main contribution of this paper is to evaluate and identify the effective measures to detect driver drowsiness and choose the best measures to combine. It will help in early detection of the driver drowsiness in a more efficient manner and avoid crashes on the roads.

Vehicle accidents due to driver drowsiness is the major problem all over the world. It leads to millions of road accidents that result in fatal and non-fatal injuries and huge financial losses. To overcome vehicle accidents and provide safety to all commuters on the roads, a smart driver drowsiness detection system is required which can detect the drowsy state of the driver at an early stage. The behavioural measure provides the promising results to detect driver drowsiness at an early stage due to its non-intrusive nature. In this measure, various facial features, ML (Machine Learning) or DL (Deep Learning) based algorithms are analyzed various states of the driver to detect drowsiness. In this paper, a comparative study has been conducted that use ML and DL based algorithms to detect driver drowsiness. This study is aimed of finding effective AI (Artificial Intelligence) approach to detect driver drowsiness at an early stage.

The product design related evolutionary transformations are strongly linked to the different geometrical dimensions. The natural process of evolution of life forms on Earth provides a blueprint for improvements in design dimensions of products. It took thousands and thousands of years for various biological varieties of plants and animals to evolve into their current form through the process of natural selection. During this long transition period, many biological species have developed a variety of geometrical shapes, inside and outside their bodies. However, there are certain geometrical patterns, which occur more repeatedly in the living creatures like plants and animals. The repeated appearance of golden ratio in a lot of life forms is evidence of its recognition by nature, in the process of evolution. The present work derives the motivation from occurrences of such mathematically defined graphics, especially the golden ratio. As an investigation, a simulation of crane hook has been created under the static stress. Two 3D models of hook have been created using Solidworks design software. One model is prepared as per the standard pre-existing proportions, and another being designed using the “golden ratio-based geometry.” Both models have been tested for “Maximum von mises stress,” under the application of same level of external pressures and forces. Stress distribution pattern in two designs were observed and compared for examining any possible significance of direct utilization of golden ratio in this product design application.

The physical security of electronic devices like laptops and tablets is vital as these devices carry confidential data which cannot be compromised. Data security can be provided through a number of innovative ways. The first line of defense is physical security. As far as physical security is concerned, there has been very little development to date. This research is focusing on the physical security of data storage devices. To provide physical security to laptop devices this work proposes a locking assembly for various electronic devices like laptops and tablets. The assembly includes a frame adapted to be coupled to a base of the one or more electronic devices. This locking assembly ensures the safety of devices against any possible theft or unauthorized usage. The design of this locking assembly presents a cost effective, easily available, and simpler to assemble, easy to manufacture and durable solution to the theft problems. A detailed analysis of the proposed design has been conducted which provided an insight of efficiency and usability of the locking mechanism. The mass properties of the model have been computed after assigning the standard material (aluminium) to various components. The mass of the locking assembly has been estimated as 0.5 Kg and the volume is 0.002 cubic meters.

Recently, protective medical equipment like face shields and face masks played a vital role during the pandemic situation. Even international health organizations also suggested using face masks and face shields. The medical equipment manufacturers were not ready to fulfill the sudden market demands due to this pandemic. As a result, medical institutions faced a shortage of such protective equipment. In this situation, additive manufacturing turned into a supplementary manufacturing process to fulfill the touchy needs and to facilitate the wellbeing around the world. This study is disclosing the present state of art with respect to face shields manufactured through additive manufacturing. This study found that face shields manufactured through additive manufacturing approach were lacking in the technology intervention and also observed that anthropometric dimensions were ignored while manufacturing such face shields. The unique contribution of this study is to propose a technological advanced face shield by introducing electronic sensors into it and that too by considering anthropometric dimensions of Indian male and female head size.

Tourism plays an important role not only as a source of generating revenue, but also is directly linked with the development local people, their growth, and generating employment. There is need for simple tourism to be converted into ecotourism. This will not only transform the place into sustainable city but also help the local people to grow. A survey was conducted in Chandigarh through a structured questionnaire, where the respondents showed significant relation between ecotourism and environmental sustainability, as well as ecotourism and social sustainability.

The world has confronted outcomes of COVID-19. It has affected every person from one corner to the other corner of this planet. The students and teachers have quickly shifted to online mode of teaching. This sudden transformation from traditional to online teaching has come up with some challenges as well as opportunities. The main objective of this study is to facilitate a device to determine the issues faced by teachers and students during online mode. An online survey is conducted to collect the issues faced by teachers during the online mode and thereafter a portable device is proposed to facilitate online learning. This is an extremely low-cost and portable device which enables the teachers to use the given canvas area just like a writing board. To find the usefulness of the device one more survey was directed among the teachers, and it has been found that the given solution is more viable while in online mode.

Remote health monitoring using Internet of Things (IoT) is a popular research area nowadays. It leads to a good improvement in the quality of life if a healthcare system is able to do accurate diagnosis remotely in minimal time. This paper represents the development and working of a pulse rate monitoring system using IoT which consists of an analog pulse rate sensor to be placed around the fingertip of the patient. Pulse rate sensor is connected to the NodeMCU ESP8266 Wi-Fi module to transfer readings to the remote server. The main purpose of this system is remote monitoring of a patient by a health professional, to check for any health abnormality based on the measured pulse rate, and make a decision for the treatment to be done. This system has good possibilities of extension for remote diagnosis of various diseases with the addition of more sensors to monitor critical health related parameters.

Background: In developing countries, the healthcare system is facing numerous challenges. One of the major challenges faced by the healthcare system is that the healthcare service providers are meager and geographically far from the densely populated area. Objective: To overcome the above challenge, the present research work proposes SHRMS (Smart Heart Rate Monitoring System) which provides the ad-hoc services to the patients who are in the transit mode in the emergency vehicle. Method: A pulse sensor is attached to the patient’s fingertip to fetch the heart rate of the patient. The patient’s data is further transmitted to the microcontroller which in turn transmits the data to the ThingSpeak cloud service. Result: SHRMS provides the real-time monitoring of the patient and helps to provide emergency aid as per the patient’s current situation. Conclusion: This device is beneficial for developing countries where the healthcare service providers are very less and geographically scattered.

Mobile computing and technology are becoming more common in many parts of private life and public services, and they are playing an increasingly important role in healthcare, not just for sensory devices but also for communication, recording, and display. They are used for more than only sensory devices but also for communications, recording, and display. Numerous medical indications and postoperative days must be monitored carefully. As a result, the most recent development in Internet of Things- (IoT-) based healthcare communication has been embraced. The Internet of Things (IoT), which is employed in a wide range of applications, is a catalyst for the healthcare industry. Healthcare data is complicated, making it difficult to handle and evaluate in order to derive useful information for decision-making. On the other hand, data security is a vital requirement in a healthcare data systems. Determining the need for a smart and secure IoT platform for healthcare applications, we create one in this study. Here, a cutting-edge encryption algorithm is used to protect the health data. Normalization is first used to preprocess the data and remove any irrelevant information. Using principal component analysis and logistic regression, the data’s features are extracted (LR-PCA). To choose the pertinent features, a feature selection process based on genetic algorithms is used. We have put out a brand-new kernel homomorphism. To increase the security of the IoT network, use the two-fish Encryption algorithm (KHTEA). EBSMO (exponential Boolean spider monkey optimization) is used to further boost the encryption process’ effectiveness. Utilizing the MATLAB simulation tool, the proposed system is assessed, and the metrics are contrasted with the accepted practices. Our suggested solution has been shown to be effective in protecting medical healthcare data. The effectiveness of the proposed and existing approaches is assessed using metrics for encryption time, execution time, and security level. The security precautions we suggested for healthcare data worked well.

advent of the internet and its impact on healthcare domain made it possible to store, access and update medical records anywhere and anytime. The term “Electronic Health Record(EHR)” refers to a digital format in which patient information is kept. Because the records are patient-centered, any authorised user can access them from any location, at any time, and from any device. Blockchain is a new technology, booming in most of the industries. Blockchain contains a number of built-in characteristics, including distributed ledger, decentralized storage, authenticity, confidentiality, and immutability and it has progressed actual applications in industries like healthcare. Blockchain achieves fortifying and averting the modification of electronic health records. Blockchain supports the quality of healthcare services to the benefits of both patients and hospitals. This paper investigates the existing techniques used in healthcare blockchain system in the domain of authentication, data integrity, and confidentiality.

This research aims for four-port MIMO antenna with very condensed size of 30×30 mm2 printed on RogersRTDuroid5880 substrate. The high speed performance of the antenna is applicable for IoT applications. The antenna is characterized in far-field with gainmax of 3.89dBi and total radiating-efficiency of 74.71%. The antenna covers wider bandwidth of 5.02GHz-13.42GHz which also makes it suitable for UWB-X band applications. The diversity key parameters such as ECC, DG, TARC and CLL are evaluated.

The most significant disturbance now affecting all economies and financial institutions is the digital transformation of economies. The world’s economy and financial institutions are digitizing at an unprecedented rate. Bitcoin is a devolved crypto-currency, or digital asset, that uses blockchain technology to expedite peer-to-peer financial transactions. Price volatility is one of the primary issues with decentralized cryptocurrencies, highlighting the need of examining the underlying price mechanism. Additionally, Bitcoin prices display non-stationary behaviour, meaning that their statistical distribution fluctuates over time. Bitcoin prices are stochastic, and no one set of characteristics can be used to forecast them completely. Nonetheless, academics have demonstrated varying degrees of effectiveness in estimating Bitcoin values using various feature sets. This article explains how to forecast Bitcoin price movements and prices using machine learning approaches. We intend to apply ARIMA, Facebook Prophet and XGBoost techniques for price prediction.

Blockchain is an emerging technology which works on decentralized peer-to-peer network and allows to make transactions securely by eliminating the need of a central authority. Blockchain is renowned for exchange of crypto-currencies but with the advent of smart contracts it is now widely used in other applications such as smart supply chain, healthcare, smart transportation, online voting, public donations, will management, buying and selling property and insurance sector. The smart contracts are digitally signed and make applications immutable and transparent. This paper is aimed at unveiling Blockchain technology, smart contracts and its applications. This paper is also disclosing the barriers in adopting Blockchain and smart contracts. The recent literature was reviewed to find the answers to the research questions. Huge power consumption, slow transaction rate, complex architecture and lack of awareness and expertise are identified as the barriers in Blockchain adoption whereas legal issues and high transaction cost are the main barriers in adopting smart contracts.

Machine learning techniques enable systems to learn Important representations from input Image data. Convolutional neural networks (CNNs) are a specific implementation of machine learning techniques and are able to create expressive representations from the input image. Hence CNNs are well suited for image processing operations such as classification, clustering, and object detection, etc. The creation of a new effectual deep CNN model involves an extensive training phase. This requires very large datasets, huge computation environments, and longer execution time. Several established deep CNNs are readily available. These networks are pre-trained on massive databases of images. VGG, ResNet, and InceptionResNetVZ are the leading pre-trained CNN models currently being used in numerous image-processing studies. Possibly we can transfer knowledge learned from such models in order to address challenges in different domains. This can be achieved by repurposing a deep CNN model as a feature generator to produce effective features for content based information retrieval applications. This research work proposes a technique for recognizing fish using deep convolutional neural networks such as ResNet-50, InceptionResNetVZ, and VGG16 that have been pre-trained using transfer learning.

COVID-19 has harmed millions of people including both patients as well as frontline health workers. There is need to protect frontline health workers as they are the backbone of healthcare system. The existing face shields worn by these workers do protect them but lacks in technology intervention. As a result, healthcare professionals are facing one major issue. The utmost issue is to measure their own body temperature at regular intervals as this process needs removal of hand gloves, PPE (Personal protective equipment) kit and face shield. This is really inconvenient and needs a safe and reliable solution. This paper is disclosing an innovative solution by offering a technologically advanced face shield capable of measuring a body temperature without the need of removing a face shield and a PPE kit. This face shield is designed in solid-works and printed within the university premises using a 3D printer. The sensors were then placed inside this 3D printed assembly. This face shield was then handed over for regular use to faculty and students of health sciences. This innovation received positive feedback from the healthcare professionals. The overall mean score of 4.59 out of 5 indicate that this product is worthy in every facet.

Detection of plant crop diseases has become an active field of research day by day due to increasing the demand for such systems and techniques as crop diseases are now become a common part of agriculture. Focusing on this demand and need, we have developed a Convolutional neural network (CNN)-based Deep learning (DL) multi-classification model which classifies the total of 900 real-time collected images of potato crop plants having healthy and potato blight (PB) disease images based on their PB disease severity level, along with this binary classification has also been done to simply classify the healthy and disease crop leaf. A total of four disease severity levels have been taken into account which resulted in a binary classification accuracy of 90.77% and 94.77% of best multi-classification accuracy. This work will be a great contribution in the field of potato disease recognition and detection using DL approaches.

A very few innovations have been noticed in the area of wheelchair production. This area is of utmost importance but yet unexplored. The innovations in this area can directly benefit disabled and old-age people and the medical staff would be the indirect beneficiaries. This research work is proposing a smart IoT enabled wheelchair cum bed keeping stability, safety, durability and affordability in mind. In addition, this research work also emphasized to make it foldable and versatile. The transformation of a wheelchair to bed and vice-versa was achieved by making use of hydraulic and linear actuators which in turn improved the patients comfort and functioning of a device. The entire system was tested in both the lab environment as well as in a real environment. A 3G Internet connectivity was used to transmit the patient’s vital parameters and to establish a face-to-face communication with a doctor. The system performed well even in a 3G environment. Thus, it can be predicted that it will perform even better in 4G environments.

Computer animations are widely used to improve comprehension. They are used in almost all disciplines. However, a poorly designed animation may not improve learning as such animations may increase the cognitive load. As a result, quite a lot of research is being focused on design principles that would be effective with respect to the cognitive load theory and can be integrated into animations to improve comprehension. This research work found the answer through a well-designed experimental study. The present study first identified effective design principles through an extensive literature review. Thereafter, an experimental study was designed in which 50 students of fourth semester of CSE (Computer Science and Engineering) participated willingly. The participants were randomly divided into two groups of 25 students each. The Group-1 was taught using modern animations, which were designed according to the selected design principles, whereas Group-2 was taught with conventional animations with auditory explanation only. A t-test was conducted on the post-test scores and found that the variances between the groups were equal (F=1.144, Sig = 0.290). Further, the two-tailed value was observed and found to be

Food Neophobia (FN) is related to individual’s fear to go for new variety of food. There may be multiple reasons for people to act as Food Neophobic and not trying something new such as ,taste, low level of knowledge etc.but it is found that Food Neophobia is directly related to low quality of diet.Social or demographical factors also plays a vital role in people liking or disliking towards food. Sometimes a bad experience also restrict people to try out new dishes. Because of all this factors generally individual restrict themselves to a particular type of food which leads to in some cases malnutrition.The aim of the study was to access the relationship between Food Neophobia with education and demographic factors in adults living in rural versus urban areas. The research carried out in Chandigarh Tri City,Punjab India.Data was collected from 441 respondents, out of which 246 respondents are females and 195 respondents were males from urban and rural classes. We found that Food Neophobia strongly influence the eating habits and directly responsible for lesser nutrition in individuals specially having high degree of Food Neophobia.

In modern society the role of Internet and computer system is well recognized. People are greatly benefited with the development of networking and cyber space but some people are using this development in unethical way to have some illegal benefits. Recently different types of Social-networking attacks are witnessed by social networking sites user. Internal Revenue Service (IRS) impersonation scams, along with technical support scams are the most common type of tricks used by the attackers on unsuspecting victims in order to achieve financial benefits. The ratio of cyber-crime in India is constantly rising due to various reasons. Cyber-crlminals are very difficult to trace and this advantage is fully utilize by scammers. In this paper an intensive review has been done on cyber-crime in India. The studies shows that fraud cases are increasing and the victims are mostly in the age group of 20 – 29 years. Mostly children and women are affected. Thus, awareness programs are required for preventing or avoiding cyber-crime in India.

Textile dyeing industries are utilizing large quantity of raw water for the processing at dyeing and finishing units. At the same time, there generate huge amount of wastewater from different processes in the textile industry. Many of textile industries in India are using variety of synthetic dyes for the processing purpose. These dyes are very complex in nature. Many dyes contain organic compounds with functional groups, carboxylic (–COOH), amine (–NH2) and azo (–N=N–). Wastewater generating from textile industry is also found to be in variety of colours along with very high COD and BOD values. Present study deals with the treatment of textile dyeing effluent with aluminium electrodes in electrochemical reactor. Experiments were carried out at different pH range (4-10) and current density 53 mA/cm2. Maximum COD and Colour removal was found 95 % and 92 % respectively at optimum pH at the cost of 13.3 Wh/dm3. Electro-coagulation was found suitable for the treatment of textile dyeing effluent.

Distillery industry is an important segment of world economy. However, a large amount of waste water generates during the alcohol production. This waste water contains very high organic load (COD ∼ 9080). Pollution regulatory agencies are very strict to maintain the standards of pollutants in treated effluent before the discharge in any water receiving body. In this context, combined technologies are very effective to manage dischargeable limit as compared to stand alone treatment process. This work is an attempt to treat distillery industry wastewater with electrochemical and chemical process by using iron as electrode. Electrochemical treatment has provided 91% chemical oxygen demand and 71.5% color reduction at pH 7, electrode gap 20 mm, current density 26 mA/cm2 and 70 min of reaction time. Whereas, in combined process of treatment maximum 97% (24.51 mg/dm3) COD reduction and 92.6 % (10.79 PCU) color reduction were achieved at mass loading of 1 g/dm3 and pH 7 with ferrous sulphate.

In recent, there has been significant development in the healthcare technology particularly due to Internet of Things (IoT). The ubiquitous computing has brought a progressive change in the field of healthcare. In this way, the wellbeing experts are serving the society in a superior manner by utilizing such IoT based gadgets. This paper presents an IoT based model “Smart Portable Intensive Care Unit” for real-time patient monitoring with an additional feature of drug delivery from the remote location. The proposed model assisting the healthcare professionals and the relatives of the patient to monitor the physiological data of the patient from the remote location. The patient’s physiological data is transmitted to the cloud. An android based mobile application is developed to fetch the patient’s data from the cloud database in real-time. The authenticity of the user is maintained throughout the data communication process. The patient’s data is transmitted on the mobile application of the doctor both in analog and digital form. The doctor can also set the flow of drug infusion from a remote location. The proposed model can be effectively used for the patients admitted in the hospital or inside the ambulance.

Blockchain is a technology that operates on distributed peer-to-peer network and is widely adopted by large number of organizations due to its attractive features such as highly secured, transparent, traceable, low transaction fee, no need of central authority and confidentiality. There are lot of confusions and myths regarding the blockchain technology as it is emerging technology and too complex in nature. This paper is aimed at revealing blockchain technology in depth along with its applications and open research challenges. The past published literature was reviewed to achieve the objectives. The study found that apart from cryptocurrency, blockchain is also suitable for other applications such as smart cities, supply chain, healthcare, smart transportation and authenticating IoT (Internet of Things) devices. This study is also disclosing various open research challenges such as scalability issues, huge power consumption and delay in completing transactions. This paper is also sharing the mitigation approaches and the future of blockchain with smart contracts.

BACKGROUND: In recent years, a lot of research work has been done to transmit vital parameters of the patient usingIOT (Internet of Things). The information related to Patient is sent by means of WBAN (Wireless Body Area Network)and sensors to the healthcare database. This has been shown a great potential to transmit vital parameter of the patient at aremote location. Remote monitoring of patient(s), including vital signs, sound and video is to be transmitted, particularlywhen a patient is in transit. By transmitting the imperative parameters of the patient to a specialist diminishes, the idealopportunity for starting treatment and permits the emergency crew to be better prepared. This will facilitate a doctor tomake a diagnostic conclusion.OBJECTIVES: This study aims to develop an advance system to transmit the vital parameters of the patient to the smartphone of the doctor at a remote location. After seeing essential parameters of the patient, the specialist can convey/endorsethe medication from the remote area.METHODS: To monitor patient’s data in real-time an android application is developed which helps the medical staff tomonitor the patient from remote location. All the patient related information is stored in Real Time Clinical Database.RESULTS: The proposed model will allow the doctors to monitor physiological parameters (HR, NIBP, Temp, ECG,SPO2) of the patient, as well as endorse medication from the remote location. This system will be helpful to providevirtual presence of the doctor inside the ambulance and to provide lifesaving drugs to the patient while the patient is intransit.CONCLUSION: The present invention provides a fully integrated system for the doctor to view the vital signs of thepatient from the remote location in real-time.

The use of natural coagulants like Moringa Oleifera and Okra plants are receiving attention for their effectiveness in waste water treatment. The technologies involved are economical, traditional and easy to implement and ideal for rural areas. The process being biological in nature does not generate any non-treatable wastes. These processes are easy to operate and require little or no maintenance. After the treatment of both the municipal and dairy waste water samples by two natural coagulants Moringa Oleifera and Okra seeds and synthetic coagulant alum, the results show that there is a reduction in the percentage of various polluting parameters like COD, BOD, turbidity, hardness, TSS and TDS etc. In the study different quantity of coagulants doses (50 mg, 200 mg, and 500 mg) were used but it is found that increasing the amount of coagulant increases the removal but it is not proportional and significant with respect to the quantity of coagulant added. By the effect of Moringa Oleifera coagulant the reduction of turbidity, COD, BOD, hardness, TSS and TDS are found to be 61.20 %, 65.3 %, 55 %, 25 %, 69 %, and 68% respectively. There is not much effect on the pH. By the effect of Okra coagulant, the reduction in percentages of turbidity, COD, BOD, hardness, TSS, and TDS are found to be 65 %, 67 %, 56 %, 30 %,72 %, and 69 % respectively. There is no significant change in pH due to natural coagulants. By the effect of alum coagulant the reduction percentages of turbidity, COD, BOD, hardness, TSs, and TDS are found to be 59 %, 59 %, 50.98%, 67 %, and 65 % respectively. The addition of alum makes the water more acidic.