A novel method of using sound waves and artificial intelligence for the detection of vehicle's proximity from cyclists and E-scooters

Outdoor air pollution has been found to have a significant adverse effect on health. When the authors attempted to monitor air quality that cyclists or e-scooter users' breath during commuting in different locations for health and safety analysis, it was found that the existence of internal combustion engine (ICE) cars has a significant effect on the pollution levels and the monitoring process. To comprehensively study the effect of cars and traffic on air quality that cyclists and e-scooters users experience, a low-cost and reliable system was needed to detect the proximity of cars that have diesel or petrol engines. Video cameras can be used to visually detect vehicles, but in the modern age with the existence of many electric and hybrid vehicles and the need to reduce the cost of instrumentation, there was a need to determine the passing of vehicles near e-scooter and bike users from the combined engine and tires sounds. To address this issue, this study suggests a novel approach of using sound waves of internal combustion engines and tire sounds during the passing of cars, combined with AI techniques (neural networks), to detect the proximity of cars from cyclists and e-scooter users. Audio-visual data was collected using Go-Pro cameras in order to combine the data with GPS location and pollution levels. Geographical data maps were produced to demonstrate the density of cars that cyclists encounter when on or near the road. This method will enable air quality monitoring research to detect the existence of ICE cars for future correlation with measured pollution levels. The proposed method allows for:•The automated selection of sensitive features from sound waves to detect vehicles.•Low-cost hardware which is independent of orientation that can be integrated with other air quality and GPS sensors.•The successful application of sensor fusion and neural networks.

Challenges and opportunities of remotely working from home during Covid-19 pandemic

The demand of online remote working from home significantly increased in 2020/21 due to the Covid-19 pandemic. This unforeseen situation has forced individuals and organisations to rapidly train employees and adopt the use of on-line working styles, seeking to maintain the same level of productivity as working from the office. The paper outlines a survey conducted amongst people working from home to identify the challenges and opportunities this change in workstyle offers. At the beginning of the pandemic, many employees faced difficulties adapting to using online tools and combining their working hours with daily routines and family commitments. However, the results show that within a short period of time the respondents had managed to develop the necessary experience and knowledge for digital working utilising tools such as collaboration platforms and video conferencing. A large proportion of respondents recognised the advantage of eliminating travelling time when working remotely from home which also has a positive impact on the environment and CO2 emissions. However, some drawbacks have been identified such as the lack of face-to-face discussion and informal meetings during working days. The Self-Determination Theory is discussed within the context of this paper and it has been found that the theory could provide an explanation of the efficient and rapid adaptation of the technology be employees.

Evaluation of Children's Screen Viewing Time and Parental Role in Household Context

Limited screen time has been recommended by the American Academy of Pediatrics for all children and no screen time for children under 2 years of age. With the advancement in technology, the prevalence and detrimental effects of excess screen time on children has become a global problem that can lead to health issues such as obesity and other cardiovascular diseases among both adults and children. This article examines the drivers of screen-related sedentary behavior within the home context and reports on parents’ attitude in supporting children’s associated behavior. The study implemented a mixed method approach of online questionnaire and face-to-face interviews. A total of 140 questionnaires, 10 semistructured interviews, and responses from parents were used to evaluate children’s behavior toward screen use and parents’ perception. The analysis of the article has shown that parents are concerned about their children’s screen time during weekends and holidays with a significant correlation between the number of hours their children spend on on-screen activities and their level of concern (P < .01). Also, for the same P value (P < .01), it has been found that there is a statistically significant positive relationship between children’s screen time and their food and beverages consumption. Children’s use of screen technology is becoming a challenge for parents as they present barriers to healthy physical activities. From the parents’ viewpoint, there is a need to change the screen use habit and this requires an appropriate intervention that promotes gratifying measures to induce more active behaviors to displace screen viewing.

Innovative algorithm to evaluate the capabilities of visual, near infrared, and infrared technologies for the detection of veins for intravenous cannulation

Intravenous cannulation is the process of inserting a cannula into a vein to administrate medication, fluids, or to take blood samples. The process of identification and of locating veins plays an important role during the intravenous cannulation procedure to reduce health care costs and the suffering of patients. This paper compares the three technologies used to assess their suitability and capability for the detection of veins to support the cannulation process. Three types of cameras are used in this study; a visual, an infrared, and a near infrared. The collected images, 103 in total, from the three technologies have been analyzed using a wide range of image processing techniques and compared with identification templates to evaluate the performance of each technology. The results show that the near infrared technology supported by suitable LED illumination is the most effective for the visualization of veins. However, infrared thermography is found to be successful when followed by a cold stimulation.