Digital Banking through the Uncertain COVID Period: A Panel Data Study

This research investigates how the uncertainty caused by the COVID-19 pandemic has affected digital banking usage in India. The study is made by utilizing a panel of data consisting of 108 firm-month observations during covid period from 2020 to 2022, with data mainly collected to analyze the impact of COVID-19 uncertainty. Most of the determinants were collected from the RBI data website. The main emphasis of this study is on the utilization of digital banking services in the context of the pandemic, and the research assesses the factors that have influenced this trend, including the number of physical bank branches, the utilization of debit and credit cards at automated teller machines (ATMs) and points of sale (PoS), as well as the level of economic policy uncertainty (EPU). The analysis was conducted using panel regression analysis, a suitable method for handling the error components in the model that are either fixed or random. The findings indicate that the uncertainty caused by the pandemic has had a negative impact on the use of digital banking services. Additionally, the study highlights that the usage of debit and credit cards at PoS has significantly contributed to promoting the progress of digital banking services during the pandemic. Overall, this study provides valuable insights into how digital banking services have evolved during a period of significant uncertainty and disruption. © 2023 by the authors.

SARS-CoV-2 Variants Impact on Key Signaling Pathways Metamorphoses into Severity

The Severe Acute Respiratory Syndrome Coronavirus-2 causes a dreadful Coronavirus Disease namely COVID-19. Respiratory system is the primary target of the virus. It also impairs other major organs such as kidney, heart, liver, brain etc. Multiple novel variants of SARS-CoV-2 have appeared since the SARS-CoV-2 pandemic occurred which are linked to increased virulence, disease transmission and severity. The virus attacks the host signalling pathways to maintain a favourable environment for its spread. The present study focuses on the comprehensive analysis of major signaling pathways affected due to several variants of SARS-CoV-2 leading to abnormalities in cell growth and differentiation. The information was curated from the weblinks of several platforms like WHO, CDC, PANGO, Nextstrain clade and GISAID clade. The data on signaling pathways and comorbidities was generated by screening of different research and review articles. SARS-CoV-2 consolidates the cytoskeleton of the host for effective cell invasion and modulates the transcription processes to enable the translation of viral protein(s). These events lead to significant increase and prolonged hyper inflammation. Further, a decreased interferon (IFN) response along with increased interleukin production leading to cytokine storm is observed. Deregulation of interleukin pathways, TNF-alpha signalling through JAK/STAT-3 signalling, MAPK1, mTOR, PI3K are few other signalling pathways that are affected on SARS-CoV-2 infection. This review represents a comprehensive analysis of the vigorous life cycle of SARS CoV-2, its different variants affecting host signalling pathways which eventually cause dysfunctioning of several organs and development of comorbidities.

Effectiveness of the chAdOx1 nCoV-19 vaccine in preventing COVID-19 infection

AIM: The study aimed to assess the effectiveness of the ChAdOx1 nCoV-19 vaccine in preventing laboratory-confirmed COVID-19. METHODS: It was a test-negative, case-control study conducted at Sharda Hospital, Greater Noida, India, between March 2021 and May 2021. An equal number of cases and controls were included in the study after taking proper informed consent. The individuals with positive reverse transcriptase-polymerase chain reaction test reports were taken as cases, whereas those with negative reports were included as controls. Data were analyzed and the groups were compared using multivariable logistic regression to calculate the odds ratio (OR), with adjustment for gender and presence or absence of comorbidities. The effectiveness of vaccine was calculated by the formula (1-adjusted OR) x100%. RESULTS: On analyzing the data from 560 case-control pairs, the vaccine effectiveness was calculated as 57.46% (95% confidence interval [CI]: 53.85-61.02) and 60.09% (95% CI: 56.32-63.77) for single dose and two doses, respectively. The effectiveness of complete and single-dose vaccination against the moderate-to-severe disease was calculated as 63.79% (95% CI: 58.58-68.77) and 56.19% (95% CI: 51.30-61.0), respectively. CONCLUSION: The ChAdOx1 nCoV-19 vaccine was found to be effective against COVID-19, with protection after two doses being a little more than that after a single dose. It also proved effective in protecting against the severe form of the disease.

Coronavirus Disease (COVID-19) Possible Transmission Routes and Alleviation Strategies

Coronavirus disease is a contagious respiratory ailment that has spread significantly around the world. Most cases of COVID-19 are spread from person to person by coming into contact with respiratory droplets that are released when an infected person coughs or sneezes. In this manuscript, we have highlighted the possible transmission of COVID-19 through food, water, air and paper. In the case of food, we have extensively covered the transmission of COVID-19 through meat, frozen foods, food packaging and food market along with the incidences worldwide. In the nextsection, we have highlighted the different components of air which are responsible for the transmission and also covered its relation with PM 2.5 incidence. The SARS-CoV-2 was isolated from sewage water/wastewater of various countries namely the United States, India, Australia, Netherlands and France signifying that wastewater can be a mode of virus transmission. The paper circulation by the infected COVID-19 patients can also be a virus conveyance route. It can be concluded that SARS-CoV-2 can therefore be transmitted indirectly through food via the workers involved in food packing or food marts.By following general safety precautions (wearing masks, using hand sanitisers, cleaning and disinfecting contact surfaces, and avoiding close contact), heating and using chemicals like ethanol (67-71%), sodium hypochlorite (0.1%) and hydrogen peroxide (0.5%) on environmental surfaces, along with vaccination, it is possible to reduce the spread of the SARS-CoV-2 virus.Copyright © 2023 The International Journal of Pharmaceutical Research and Allied Sciences (IJPRAS).

A novel cystic fibrosis-pregnancy service: Two-year review after introduction of elexacaftor/tezacaftor/ivacaftor

Background: As a quality service improvement response since elexacaftor/ tezacaftor/ivacaftor (ELX/TEZ/IVA) became available and the yearly average number of cystic fibrosis (CF) pregnancies (n = 7 pre-2020, n = 33 in 2021) increased significantly at an adult CF center (~600 people with CF), a monthly multidisciplinary CF-maternal health virtual clinic was established with antenatal virtual CF exercise classes dedicated to providing adaptive, specialist support to this cohort, aswell as outreach guidance and education to local obstetric teams. Method(s): This was a single-center retrospective reviewof Royal Brompton Hospital CF-Maternal Health multidisciplinary team clinic records and a patient survey from March 2020 to March 2022. Result(s): Of 47 pregnancies in 41 women (median age 30;) eligible for ELX/ TEZ/IVA at start of pregnancy, 40% (n = 19) were unplanned, and 19% (n = 9) used assisted conception. Three women with a history of infertility conceived naturally, having required assisted conception for previous pregnancies, and five women had multiple pregnancies during the study period. ELX/TEZ/IVA was continued in 60% (n = 28), delayed in 28% (n = 13), and stopped in 13% (n = 6) of pregnancies through maternal choice and careful clinical counselling. Pre-pregnancy pulmonary status was poorer in women who continued than in those who delayed or stopped (Table 1). Of those who stopped, 85% (n = 5) restarted because of pulmonary deterioration by the third trimester. Prenatal CF complications included at least one episode of minor hemoptysis in 21% (n = 9/41) of women, at least one infective exacerbation in 55% of pregnancies (n = 26/47), and noninvasive ventilation in one woman. Other pregnancy-associated complications included one case of ovarian hyperstimulation syndrome, one case of sub-segmental pulmonary embolism, and two cases of pregnancy-induced hypertension. Excluding 10 first trimester terminations, 10 current pregnancies, and one patient relocation, obstetric outcomes available for 26 pregnancies confirmed a live birth rate of 85% (n = 22/26) and a 15% first-trimester miscarriage rate (n = 4). Obstetric complications included preterm delivery rate of 23% (n = 6/26), including two cases of COVID infection resulting in two neonatal intensive care unit admissions, one case of endometritis after cesarean section, and a fourthdegree perineal tear. There were no ectopic pregnancies, maternal or neonatal deaths, or reports of infant cataracts or congenital malformations. Median gestational age was 37/40 weeks (range 29-40). Mode of delivery was via cesarean section in 45% (n = 10/22, of which twowere emergency) and vaginal in 55% (n = 12/22), of which 83% (n = 10/12) were via induction of labor for diabetes (CF or gestational) indication. Deliveries were supported and occurred equally at local obstetric units and in tertiarycare obstetric hospital settings (50%, n = 11/22). Patient-experience survey responses cited high levels of confidence in health optimization and prioritization during pregnancy and praised excellent inter-health care provider communication and peer-to-peer emotional support provided among expectant mothers in the virtual prenatal exercise groups. Table 1. Baseline demographic and clinical characteristics of elexacaftor/tezacaftor/ivacaftoreligible expectant mothers according to therapeutic decision (Table Presented) Conclusion(s): In the absence of clinical trial safety data, the novel approach of a dedicated CF-maternal health multidisciplinary team clinic with local obstetric outreach support has ensured regular specialist clinical and emotional peer-to-peer support for this cohort of women eligible for ELX/ TEZ/IVA to ensure optimal outcomes and experiences of their pregnancies, where appropriate, close to home.Copyright © 2022, European Cystic Fibrosis Society. All rights reserved

Analysis of Student Study of Virtual Learning Using Machine Learning Techniques

Since COVID-19 was released, online education has taken center stage. Educational performance analysis is a central topic in virtual classrooms and across the spectrum of academic institutions. This research analyzed students' studies in virtual learning using many machine-learning classifiers, which include LogitBoost, Logistic Regression, J48, OneR, Multilayer Perceptron, and Naive Bayes, to find the ideal one that produces the best outcomes. This research evaluates algorithms based on recall, precision, and f-measure to determine their efficacy. Accordingly, the authors try to perform a comparative analysis of the algorithms in this research by employing two distinct test models: the use of training sets and the 10 cross-fold models. The research results demonstrate that the training set model outperforms the 10 cross-fold model. The findings demonstrate that the multilayer perceptron classifier utilizing the use training set model performs much better in terms of predicting student study in virtual learning.

E-Adoption of Emerging Technology in the Health Sector During COVID-19

In the 21st century, COVID-19 made a profound impact on the world. This pandemic had a detrimental impact worldwide, causing massive economic damage and enormous mortality. Emerging technologies play an essential role in every sector, and the health sector is not exceptional in this line. This paper examines the health sector before, during, and after the COVID-19 era by taking a view of emerging technologies. Artificial intelligence, cloud computing, IoT, learning paradigms, blockchain, and others are emerging technologies. E-adoption of these technologies becomes important to face critical situations during COVID-19. Using these technologies, it is possible to care for and monitor remote patients by keeping medical record management. This study includes a brief examination of similar work. In addition, the impact of e-adoption on health sector is discussed in this research. Furthermore, this study suggested a paradigm for comprehending the application of developing technologies to manage and overcome the health sector???s burden. Finally, research is concluded with remarks on the future.

Advances in encapsulation of organic compounds for biological protective textiles

Humans are surrounded by numerous pathogens, which can cause severe infections and even become a source of death. The world has seen the impact of COVID-19 on the health and economic sector and continues to see the other impact if corrective measures are not taken. Similarly, the impact of bacteria on the human body has increased noticeably over the past few years, and is one of the significant challenges the healthcare sector faces. Therefore it is imperative to focus on the systems through which the impact of pathogens could be reduced. Scientists are rigorously working on the development of biological protective textiles using the encapsulation of organic compounds to protect the user from harmful pathogens. This chapter will review recent advancements in the development of biological protective textiles using encapsulated organic compounds. The fundamentals of micro/nanoencapsulation and the most important encapsulation techniques used for the development of microcapsules loaded with organic compounds (essential oils) will be described. The application of various organic compounds onto textiles through suitable encapsulation techniques will also be discussed. The control-release kinetics with mathematical modeling will be thoroughly discussed to understand the release behaviors of microcapsules. Novel biological protective textiles such as antiviral, antibacterial, antifungal, antioxidant, mosquito repellent, insect repellent, etc., will be reviewed. Finally, the mode of action of essential oils against viruses, pathogens, insects, mosquitoes, and oxidants will be explained. © 2023 Elsevier Ltd. All rights reserved.

Investigation of seroprevalence of SARS-CoV-2 IgG antibodies among healthcare workers in a tertiary care centre in district Amritsar

Background: SARS-CoV-2 infection poses tremendous challenge to the healthcare system of nations across the globe. Healthcare workers (HCWs) are crucial to the ongoing response to the SARS-CoV-2 pandemic. During the course of their work, they are exposed to hazards that place them at the risk of infection. Serological testing for SARS-CoV2 among healthcare workers, which form a high risk group helps in identifying the burden of hidden infection in an institutional setting. The present study aims to investigate the seroprevalence of IgG antibodies against SARS-CoV-2 among HCWs during 1st and 2nd wave. Material & Methods: A prospective study was conducted at Viral Research and Diagnostic Laboratory, Government Medical College, Amritsar during June July 2020 (1st wave)and April May 2021(2nd wave). During this period, 184 blood samples were collected from healthcare workers from Government Medical College and Hospital, Amritsar. Serum was separated and used for detection of Anti-SARS-CoV-2 IgG antibodies by ELISA technique. Results: Out of the 184 samples, 79 (42.9%) were found to be seropositive. Higher seropositivity was seen i.e 60.8% during the 2nd wave (April-May 2021) as compared to 25% during 1st wave. The increase in seroprevalence was observed in almost all categories of HCWs, Doctors 44.4% vz 13.04%, nurses 54.8% vz 34.7%, lab technicians 72% vz 30.4% and housekeeping staff 72.2% vz 21.7%. Also the unvaccinated HCWs showed higher seroprevalence during the second wave and 87.5% of vaccinated HCWs had demonstrable IgG antibodies. Conclusions: High seropositivity was observed among healthcare workers due to their nature of work. Rise of seropositivity among unvaccinated HCWs during 2nd wave concludes that increase in seroprevalence was attributable to natural infection. The vaccine's immunological response was also highlighted in the study.

Attention-Based Deep Learning Approach for Semantic Analysis of Chest X-Ray Images Modality

The world today is suffering from a huge pandemic COVID-19 that has infected 106M people around the globe causing 2.33M deaths, as of February 9, 2021. To control the disease from spreading more and to provide accurate healthcare to existing patients, detection of COVID-19 at an early stage is important. As per the World Health Organization, diagnosing pneumonia is a common way of detecting COVID-19. In many situations, a chest X-ray is used to determine the type of pneumonia. However, writing a report for every chest X-ray becomes a tedious and time-taking task for physicians. We propose a novel method of creating reports from chest X-rays images automatically via a deep learning model using image captioning with an attention mechanism employed through CNN–LSTM architecture. On comparing the model that does not use an attention mechanism with our approach, we found that accuracy was increased from 80% to 87.5%. In conclusion, we found that results generated with attention mechanism are better, and the report thus produced can be utilized by doctors and researchers worldwide to analyze new X-rays in lesser time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Novel Machine Learning Classification Model to Analyze the COVID-19 Pandemic's Impact on Academics: Sentiment Analysis Approach

The COVID-19 Pandemic is considered as the worst situation for human beings;it affected people's lives worldwide. Due to this pandemic, the respective government authority announced the lockdown to break the coronavirus chain. The lockdown impacted people's mental health, leading to many psychological issues as well as hampered students' academics. In this chapter we have studied the impacts on students' academics due to lockdown effect. The data has been collected via a google form questionnaire circulated to various educational institutes. Further, we have developed a novel machine learning classifier model called Naïve Bayes-Support Vector Machine for analyzing the data, which utilizes the properties of both classifiers by using a deep learning framework. We have used natural language processing (TextBlob, Stanza and Vader) libraries to label the dataset and applied in the proposed NBSVM method and other machine learning models and classified the sentiments into two categories (Positive vs Negative). We also applied the natural language processing libraries used a topic-modelling technique called Latent Dirichlet Allocation to know the essential topics words of both classes from students' feedback data. The study revealed 83% and 86% accuracy for unigram and bigram, respectively, whereas the precision was 79% and recall 81%. According to NLP libraries' result, approximately 71% of the feedback's sentiment is negative, and only 16% of feedbacks are positive. The proposed model shown that (Naïve Bayes-Support Vector Machine) outperforms the other variants of the Naïve Bayes and support vector machine. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Modern Mortuary Complex Plan in Covid-19 Era

The COVID-19 pandemicis the most burning health emergency worldwide now a days and all health professionals are called to give support in the diagnosis, treatment of patients and management of dead bodies affected by this disease. Different modes of transmission of corona virus is well established, however aerosol generating procedure has significant importance for mortuary during autopsy. The risk of infection can be minimized by using standard universal precautions for autopsy dissection procedure, applying high bio-safety levels, using negative pressure and laminar flow system for ventilation, UV irradiation for sterilization, virtual autopsy etc. The aim can be achieved by constructing the mortuary complex in more planned way like area division, ventilation planning, environmental disinfection, individual protection, autopsy procedure, virtual autopsy, preservation and transportation of dead body and waste disposal management. The present manuscript describes in detail about modern mortuary complex during the pandemic era of covid-19 © 2022, Journal of Indian Academy of Forensic Medicine.All Rights Reserved.

Embracing Covid-19 pandemic: Entrepreneurship within the Indigenous context

Resilience implies a continuous transformation process and learning through a crisis. The study aims to identify the role of resilience during the Covid-19 pandemic. To identify the most challenging transformations of the entrepreneurs, we explored the extent to which business models were altered through the first and second Covid-19 lockdowns. The narrative research design was adopted to provide insights into entrepreneurs' thoughts, emotions, and interpretations' by taking on the stories of seven indigenous entrepreneurs of India. Social capital (family and community) and problem-focused coping gained prominence in developing the resilience of the indigenous entrepreneurs throughout the crisis, while emotion-focused coping emerged as the initial strategy utilized against the crisis. © 2022, Pro Global Science Association. All rights reserved.

A Perceptional Shift From Online To Offline Education: An In-Depth Analysis Of The Student's Mindset

The covid-19 pandemic has emerged as the most severe health challenge since the end of the 1918 Spanish flu. With the social distancing norms and travel restrictions in place, the education sector has radically changed. The students have continued their studies in virtual mode for the past two years. But after the pandemic, the pupils must return to their old lives. The objective of this paper is to find out how this change affects the students mentally and whether attending classes offline is taking a toll on them. Are they feeling more stressed compared to when they were online, and is the change affecting their academic performance? This paper will analyse the psychological effects of a change in the environment of a student's life and try to answer what will be the best solution to the problems caused therein. Copyright © 2022, Anka Publishers. All rights reserved.

Effects of SARS-Cov-2 infection and rhino-orbital mucormycosis on concentrations of inflammatory biomarkers in Indian populations

Rhino-orbital mucormycosis is a rare life threatening invasive fungal infection that has recently shown a very high mortality rate in India during COVID-19 pandemic. We have designed the present study to find out associations between COVID-19 induced rhino-orbital mucormycosis and concentrations of inflammatory markers, i.e. D-dimer, Ferritin, IL-6, CRP and PCT, in blood serum of Indian population. There were four groups in the study, viz. control group with healthy subjects, treatment group-1 with patients suffering from SARS-COV-2 infection, treatment group-2 with patients suffering from both SARS-COV-2 infection and rhino-orbital mucormycosis, and treatment group-3 with patients suffering from rhino-orbital mucormycosis after SARS-COV-2 infection recovery. Inflammatory markers were quantified with standard protocols, and recorded data were subjected to statistical analyses. We found that patients suffering from SARS-COV-2 infection were more susceptible to rhino-orbital mucormycosis, as they had higher concentrations of inflammatory markers in their blood than the other subjects. Diabetes mellitus, hypertension, cardiovascular diseases and renal disorders were the associated comorbidities with the patients. We also found higher concentrations of inflammatory markers in males than the females, indicating towards their higher susceptibility in developing rhino-orbital mucormycosis than females. Present study therefore suggests that the frequent occurrence of rhino-orbital mucormycosis in India during second wave of COVID-19 was possibly due to indiscriminate use of corticosteroids by COVID-19 patients. Subjects with previous history of comorbidities like diabetes mellitus, hypertension, cardiovascular disorders and renal diseases are the most susceptible population groups for developing infection. Moreover, males are at higher risk of developing mucormycosis than the females. © 2022 Innovative Publication, All rights reserved.

Awareness about transmission and preventive measures of COVID-19 from mother to child: A cross-sectional study among pregnant women

Objective: To study the knowledge, attitude, and practice of pregnant women regarding transmission and preventive measures of COVID-19 from mother to child and to determine the reasons for vaccine hesitancy. Method(s): This observational cross-sectional knowledge, attitude, and practice study was conducted among pregnant women of any trimester, attending the antenatal care out-patient department of a tertiary care hospital in Lucknow from October 2020 to March 2021. All the participants were interviewed using a pretested semi-structured questionnaire for desired information. Reasons for vaccine hesitancy were also asked to assess their unwillingness to get vaccinated. Result(s): Totally 652 pregnant women were included and 91.3% were aware that COVID-19 spread through contact with an infected person and 85.3% knew that COVID-19 spread by respiratory droplets. Of pregnant women, 95.7% perceived that social distancing and wearing a proper mask were effective ways to prevent SARS-CoV-2 infection and 96.8% of the pregnant women wore masks regularly when going out. Of pregnant women, 79.0% were hesitant to get vaccinated. The most common reason was that COVID-19 vaccine can harm the developing fetus (77.5%) and was not very safe in pregnancy (75.0%). Conclusion(s): Of the pregnant women, 22.92% have unsatisfactory knowledge regarding COVID-19, 35.63% have negative attitude and 19.93% have poor practices, indicating that there are still gaps in awareness, and majority of them are unwilling to get vaccinated. Good awareness will help prevent the occurrence of future COVID-19 waves in India. Copyright © 2022 Asian Pacific Journal of Reproduction.

Women perspective of shifting paradigms towards online shopping

Online shopping is a method of purchasing goods and services from the comfort of one's own home, office, or any other location with internet access. It is the shifting paradigm of offline to online shopping scenario, specially in the Covid era when everybody in the whole world were forced to stay at their homes to be safe and movement was allowed only to buy groceries for stipulated period. The purpose of this study is to analyze the shifting paradigm of shopping from offline to online from the women perspective. The judgmental non probability sampling approach was used to gather cross-sectional primary data from online and offline women shoppers of the country. The questionnaire is prepared with the help of a literature review and experts. In order to understand the preferences of customer, discriminant analysis is applied on the collected responses of 200 women customers from metro cities of the country using SPSS software. The response data consists of the ratings provided by the women consumers for the different mode of shopping. It is compared with the help of Descriptive Statistics, Discriminant Analysis, Wilks Lambda, F stats and its p value. In the study the fifteen attributes are considered for comparing the preferences of women for shopping and found that out of fifteen attributes eight attributes are considered by women customers for online shopping, six for offline and in one attributes their preferences for online and offline shopping is almost same.

Present and future challenges in therapeutic designing using computational approaches

Currently, various computational methods are being used for the purpose of therapeutic design. The advent of the Coronavirus disease-2019 (COVID-19) pandemic has created a lot of problems due to which the development of effective treatment options is urgently needed. Computational intelligence is used in the control, prevention, prediction, diagnosis, and treatment of the disease. Several important drug targets have been identified in severe acute respiratory syndrome-Coronavirus-2 using in silico methods. Computer-aided drug design includes a variety of theoretical and computational approaches that are part of modern drug discovery. Advances in machine learning methods and their applications speed up the drug discovery process. Exploration of nucleic acid-based therapeutics is playing an important role in healthcare also. But a lot of challenges have also been seen that complicate the therapeutic design. Therefore, investigation of challenges associated with therapeutic design is important, and the present chapter is aimed to cover various therapeutic design approaches and challenges associated with them. Moreover, the role of computational strategies in the exploration of potential therapeutics against COVID-19 has been investigated. © 2022 Elsevier Inc. All rights reserved.

Assessing Micro-Mobility Services in Pandemics for Studying the 10-Minutes Cities Concept in India Using Geospatial Data Analysis: an Application

Active micro-mobility decreases traffic, bolsters personal health, and helps communities thrive by protecting the environment Moreover, sustainable micro-mobility demand is expected to get boosted in the present and post-COVID society. In this work we highlight the micro-mobility modes of walkability and bicycling to city administrators controlling urban city-space, by adapting the mobility parameters and their use cases through a map-based interface. Software tools and web-based applications are introduced for easy policy decisions by city managers. Present study scope is circumscribed by exploration of different parameters in traditional and state of art data science models, for resource planning like cycle usage prediction and planning. These parameters show hazard safe-distance pedestrian flow, optimal resource planning, amenity reach (10 min cycling and walking distance) and mobility using walking and cycling modes. Parameters of the traditional Social Force Model for Pedestrian Dynamics are also inspected, according to COVID social norms, to capture safe pedestrian flow density. Finally, the analysis of two case studies, of Bhubaneshwar city and New Delhi, in India, are discussed for policy suggestions to enhance mobility via sustainable micro-mobility modes. The developed system assists managers in decisions based on urban data intelligence, and at user end eases commute related mental tension, anxiety and dependencies. The developed application is running live on our server maintained at Edinburgh University. © 2022 ACM.