A LowCost Breath Analyzer Module in Domiciliary NonInvasive Mechanical Ventilation for Remote COPD Patient Monitoring Smart Breath Analyzers were developed as sensing terminals of a telemedicine architecture devoted to remote monitoring of patients suffering from Chronic Obstructive Pulmonary Disease (COPD) and homeassisted by noninvasive mechanical ventilation via respiratory face mask. The devices based on different sensors (CO2O2 and Volatile Organic Compounds (VOCs), relative humidity and temperature (R.H. u0026 T) sensors) monitor the breath air exhaled into the expiratory line of the bitube patient breathing circuit during a noninvasive ventilotherapy session; the sensor raw signals are transmitted pseudonymized to National Health Service units by TCPIP communication through a cloud remote platform. The work is a proofofconcept of a sensorsbased IoT system with the perspective to check continuously the effectiveness of therapy andor any state of exacerbation of the disease requiring healthcare. Lab tests in controlled experimental conditions by a gasmixing bench towards CO2O2 concentrations and exhaled breath collected in a sampling bag were carried out to test the realized prototypes. The Smart Breath Analyzers were also tested in real conditions both on a healthy volunteer subject and a COPD suffering patient.

Internet of Things and Enhanced Living Environments: Measuring and Mapping Air Quality Using Cyberphysical Systems and Mobile Computing Technologies This paper presents a realtime air quality monitoring system based on Internet of Things. Air quality is particularly relevant for enhanced living environments and wellbeing. The Environmental Protection Agency and the World Health Organization have acknowledged the material impact of air quality on public health and defined standards and policies to regulate and improve air quality. However, there is a significant need for costeffective methods to monitor and control air quality which provide modularity, scalability, portability, easy installation and configuration features, and mobile computing technologies integration. The proposed method allows the measuring and mapping of air quality levels considering the spatialtemporal information. This system incorporates a cyberphysical system for data collection and mobile computing software for data consulting. Moreover, this method provides a costeffective and efficient solution for air quality supervision and can be installed in vehicles to monitor air quality while travelling. The results obtained confirm the implementation of the system and present a relevant contribution to enhanced living environments in smart cities. This supervision solution provides realtime identification of unhealthy behaviours and supports the planning of possible interventions to increase air quality.