Air pollution, climate change, and chemical exposure constitute the world's most significant environmental health concern, resulting in the early deaths of 6. 5 million people annually. Reducing child mortality from preventable causes, primarily pneumonia and other respiratory illnesses, would have contributed to the united nation's sustainable development goals (SDG). Some significant goals are sustainable cities, industry innovation, green and resilient infrastructure, good health, and well-being. Non-ventilator hospital-acquired pneumonia (NV-HAP) is a severe but preventable cause of morbidity and mortality in hospitalized patients. Despite being the most frequent and fatal hospital-acquired infection (HAI), NV-HAP is not tracked, documented, or avoided in most hospitals. The success of NV-HAP prevention and monitoring initiatives relies on reliable, up-to-date surveillance data. Surveillance offers the information needed to target, analyze, and quantify the efficacy of preventative activities by identifying patients at the highest risk for NV-HAP. However, pneumonia monitoring is complex due to the clinical criteria's subjective, imprecise, inconsistently recorded, and labor-intensive nature. Non-ventilator hospital-acquired pneumonia must be monitored and standardized, which demands cutting-edge technologies and the deployment of advanced sensors. In the framework of this research, initially, a wireless body area networks (WBANs) architecture has built by making use of wearable biosensors, and then real-time sensor data were uploaded to a cloud platform. Researchers have devised a wireless sensor network (WSN) to track volatile organic compounds (VOC) and other atmospheric characteristics in real time to curb the spread of NV-HAP. The ESP32 Internet of Things (IoT) and Raspberry Pi 4B graphical processing unit platforms host the finalized WBAN and WSN network. To reduce the mortality rate of NV-HAP, this research aims to investigate clinics' and hospitals' indoor and outdoor air quality. The developed biosensor-assisted IoT enabled framework is used in hospitals to keep tabs on the conditions of individual patient rooms, treatment areas, and critical care units in real time. The research found the suggested technique achieves better results than existing state-of-the-art methods regarding computing cost, communication overhead, storage cost, and energy utilization.