Health and safety considerations of room occupants in enclosed spaces is crucial for building management which entails control and stringent monitoring of co 2 levels to maintain acceptable air quality standards and improve energy efficiency. Smart building management systems equipped with portable, low-power, non-invasive co 2 sensing techniques can predict room occupancy detection based on co 2 levels exhaled by humans. In this work, we have demonstrated the development and proof-offeasibility working of an electrochemical RtiL-based sensor prototype for co 2 detection in exhaled human breath. The portability, small form factor, embedded RTIL sensing element, integrability with low-power microelectronic and iot interfaces makes this co 2 sensor prototype a potential application for passive room occupancy monitoring. This prototype exhibits a wide dynamic range of 400-8000 ppm, a short response time of ~10 secs, and a reset time of ~6 secs in comparison to commercial standards. The calibration response of the prototype exhibits an R 2 of 0.956. With RTIL as the sensing element, we have achieved a sensitivity of 29 pF/ppm towards CO 2 at ambient environmental conditions and a three times greater selectivity towards co 2 in the presence of n 2 and o 2. CO 2 detection is accomplished by quantifying the capacitance modulations arising within the electrical double layer from the RtiL-co 2 interactions through Ac-based electrochemical impedance spectroscopy and Dcbased chronoamperometry. Monitoring of CO 2 levels has been a crucial subject of research interest worldwide in regard to efficient building occupancy management for indoor occupancy comfort and energy-savings 1. In the US, indoor air quality monitoring and occupancy comforts account for 40% of the total energy usage 2. Intelligent buildings have adopted system controls that communicate with the deployed sensor network within the building to optimize occupancy comforts and energy consumption. IOT based sensor technology is gaining attraction and has made its way into building management systems to monitor vital indoor environmental parameters such as acoustics, CO, VOC, small particulate matter, CO 2 , temperature, and humidity. Information collected from all these sensors can be utilized to predict patterns for preventing mishaps and take corrective actions in advance for effective building maintenance 3. The smart sensor network should be capable of automatically modulating its air ventilation to avoid excessive ventilation for energy savings in areas with highly variable and dense occupancy 4. Exhaled human breath is the main source of CO 2 production in indoor spaces and is a widely used indicator of room occupancy. CO 2 is regarded as a toxic contaminant with acceptable exposure limit of 5000 ppm over an 8-hour window or a short exposure limit of 15,000-30,000 ppm for 15-minutes according to OSHA and ASHREA standards. The CO 2 levels produced by humans are much higher than the CO 2 present in outdoor environment. Studies show that the indoor CO 2 concent...