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Background/AimsThe COVID-19 has facilitated a paradigm shift in the sphere of ophthalmic telemedicine: its utility is no longer limited to providing care to remote regions, rather it is expeditiously being adopted as the new standard of care. The aim of our paper is to explore the current attitudes of oculoplastic surgeons towards telemedicine and its utility in the present landscape and its prospects in the future.MethodsA 39-item questionnaire was distributed to consultant oculoplastic surgeons practising across the UK and anonymised responses were collected and analysed.ResultsThe COVID-19 pandemic has allowed rapid implementation of telemedicine services in oculoplastic departments across the UK with 86.6% of the respondents incorporating telemedicine into the routine clinical practice. Clinicians reported a statistically significant increase in utility of telemedicine, confidence in using telemedicine and quality of infrastructure available to employ telemedicine following the COVID-19 outbreak. The greatest utility of telemedicine is in triaging, postoperative assessment and eyelid lesion assessment. Main barriers to implementation of telemedicine included difficulties in conducting clinical examinations, lack of administrative support and poor access to digital technologies for patients. Overall, most clinicians were satisfied with the impact of telemedicine services and almost all experts foresee themselves continuing to use telemedicine in the future.ConclusionsTelemedicine has become an integral part of the oculoplastic service delivery since the COVID-19 pandemic its use is likely to continue. Further development of digital infrastructure and improvement of clinical examination capabilities are required to enable its wider adoption.

In this research, a weather forecasting model based on machine learning is proposed for improving the accuracy and efficiency of forecasting. The aim of this research is to propose a weather prediction model for short-range prediction based on numerical data. Daily weather prediction includes the work of thousands of worldwide meteorologists and observers. Modernized computers make predictions more precise than ever, and earth-orbiting weather satellites capture pictures of clouds from space. However, in many cases, the forecast under many conditions is not accurate. Numerical weather prediction (NWP) is one of the popular methods for forecasting weather conditions. NWP is a major weather modeling tool for meteorologists which contributes to more accurate accuracy. In this research, the weather forecasting model uses the C5.0 algorithm with K-means clustering. The C5.0 is one of the better decision tree classifiers, and the decision tree is a great alternative for forecasting and prediction. The algorithm for clustering the K-means is used to combine identical data together. For this process, the clustering of K-means is initially applied to divide the dataset into the closest cluster of K. For training and testing, the meteorological data collection obtained from the database Modern-Era Historical Analysis for Research and Applications (MERRA) is used. The model's performance is assessed through MAE mean absolute error (MAE) and root mean square error (RMSE). And the proposed model is assessed with accuracy, sensitivity, and specificity for validation. The results obtained are compared with other current machine learning approaches, and the proposed model achieved predictive accuracy of 90.18%.

For visually impaired people, a cane is a close companion helping them to detect and avoid obstacles while walking. But while walking in a new or changed environment, it is hard for them to guess where they are. Also it will be a problem when they lose memory of locations and places. The standard method for taking notes by visually impaired is to emboss Braille dots on a paper, which can be read by feeling the dots by fingers [16]. It is difficult to imprint, copy, transfer or edit these writings. With the advancement in modern day electronic sensors, touch sensing and microcontroller technology, the proposed system aids the visually impaired in navigation via audible messages and haptic feedback, helping them localize where they are and to improve their mobility. This system supports the visually impaired to enter notes and control device operation via touch keypad. The device also provides user information in audio format, including navigation direction, ambient light and temperature condition. The aim of this project is to help visually impaired to improve their communication and provides independency during walking in even unknown areas.