Injuries due to fall or vehicle accident, including bikes or bicycles are relatively common. One of the reason for a person severe health menace after an accident is the unavailability of first aid, due to the delay in informing about the accident. Thus, in the case of incidents involving vehicle accidents or falls, response time is crucial for the timely provision of emergency medical services to the victims of accidents. An effective approach intended to reduce the number of falls-related deaths is: the use of a system for detecting and reporting the occurred accidents, as well as reducing the time between the occurrences of an accident and sending the first emergency respondents to the scene of the accident. This paper presents a solution using mobile terminals (smartphones) for detecting and preventing accidents like falls.

The amount of moisture in the air is represented by relative humidity (RH); an ideal level of humidity in the interior environment is between 40% and 60% at temperatures between 18° and 20° Celsius. When the RH falls below this level, the environment becomes dry, which can cause skin dryness, irritation, and discomfort at low temperatures. When the humidity level rises above 60%, a wet atmosphere develops, which encourages the growth of mold and mites. Asthma and allergy symptoms may occur as a result. Human health is harmed by excessive humidity or a lack thereof. Dehumidifiers can be used to provide an optimal level of humidity and a stable and pleasant atmosphere; certain models disinfect and purify the water, reducing the spread of bacteria. The design and implementation of a client-server indoor and outdoor air quality monitoring application are presented in this paper. The Netatmo station was used to acquire the data needed in the application. The client is an Android application that allows the user to monitor air quality over a period of their choosing. For a good monitoring process, the Netatmo modules were used to collect data from both environments (indoor: temperature (T), RH, carbon dioxide (CO₂), atmospheric pressure (Pa), noise and outdoor: T and RH). The data is stored in a database, using MySQL. The Android application allows the user to view the evolution of the measured parameters in the form of graphs. Also, the paper presents a prediction model of RH using Azure Machine Learning Studio (Azure ML Studio). The model is evaluated using metrics: Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE), Relative Squared Error (RSE) and Coefficient of Determination (CoD).

Traffic growth, traffic noise in cities, rising cities, industrialization, economic development, increase energy consumption and population growth in urban areas leads to global warming and acid rain. Taking into account all of these factors, the continuous monitoring of air quality is essential. Due to the fast growth of vehicles number, the routing in urban traffic becomes one of the most important problem in pollution avoidance and the decrease of the noise traffic too. This paper presents a solution for minimizing the CO ₂ footprint based on traffic control in urban areas, using small and portable devices. Other parameters which can be measured with this device are: temperature, humidity, atmospheric pressure, light and Total Volatile Organic Compounds. For this purpose, a demonstration mobile application has been developed. The mobile application displays and analyzes data provided by beacons. Paper present a low-cost solution for monitoring and in the future a traffic optimization. The first step would be to assemble the device proposed on all means of public transport and in major stores.

This paper presents a software solution for monitoring people in quarantine during a pandemic. The development of the software solution presented in this paper aims to streamline the measure of isolation at home or quarantine centers. Persons affected by this measure must not leave the quarantine area in any form within the time limit set by the authorities. This software solution proposes a solution by which these people can be monitored by requesting their current location at a specified time interval. This solution assists the competent authorities by eliminating the need to verify quarantined persons by authorized personnel. Thus, those resources can be used for other pandemic prevention purposes.