Degrading air quality is a matter of concern nowadays, and monitoring air quality helps us keep an eye on it. Air pollution is a pressing global issue with far-reaching impacts on public health and the environment. The need for effective and real-time monitoring systems has become increasingly apparent to combat this growing concern. Here, an innovative air pollution surveillance system (APSS) that leverages Internet of Things (IoT) technology to enable comprehensive and dynamic air quality assessment is introduced. The proposed APMS employs a network of Io enabled sensors strategically deployed across urban and industrial areas. These sensors are equipped to measure various pollutants, including particulate matter (PM2.5 and PM10), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO), and volatile organic compounds (VOCs). Here, a regression model is created to forecast air quality using sensor data while taking into account variables including weather information, traffic patterns, and pollutants. Additionally, air quality categories (such as good, moderate, and harmful) are classified using classification algorithms based on preset thresholds. The IoT architecture facilitates seamless data transmission from these sensors to a centralized cloud-based platform. The developed APSS monitors the air quality using an MQ-135 gas sensor, and the data are shared over a web server using the Internet. An alarm will trigger when the air quality goes below a certain level. Also, the air quality, which is measured in parts per million (PPM), is displayed on the unit connected to it. Furthermore, when the PPM goes beyond a certain level, an alert message is sent to the air pollution control board, which takes preventive measures to control the pollution and also alerts the people, which helps each person in that society save their environment from pollution and have a good air quality environment. Additionally, the APSS offers user-friendly interfaces, accessible through web and mobile applications, to empower citizens with real-time air quality information. The effectiveness of the IoT-based air pollution monitoring system has been validated through successful field trials in urban and industrial environments, and it has the ability to provide real-time data insights and empower stakeholders in promoting environmental sustainability and fostering citizen engagement.

The increasing demand for sustainable and safe mobility has driven research on hybrid electric bicycles, with particular attention to women’s safety in urban areas. This work introduces a hybrid bicycle design that combines solar and pedal-powered energy harvesting with advanced safety mechanisms. A boost converter ensures stable energy management by regulating voltage from renewable sources and supporting auxiliary functions like lighting, health monitoring, and communication systems. A permanent-magnet brushless DC (PMBLDC) motor is employed for higher efficiency, low maintenance, and enhanced torque. Safety features such as fingerprint authentication, GPS, GSM-based alerts, and a panic button promote independent and secure commuting for women. Simulations confirm reliable performance for both pedaling and solar energy harvesting. A 12 V battery, an MPPT controller, and a 9 V solar panel are used in the solar energy harvesting system. Hardware tests validate real-time operation, including solar charging, battery storage, and safety alerts, with solar energy delivering 6 V/h and pedaling contributing 0.09 V/min. The system’s viability is confirmed by hardware implementation and testing, which demonstrate efficient solar and pedaling energy collection, dependable motor performance, and operational safety alerts. The system addresses energy instability while ensuring a compact design and embedded security, making it a cost-effective, sustainable, and socially relevant solution.