# Beyond Control: Enabling Smart Thermostats For Leakage Detection

## TL;DR

This paper introduces Greina, a novel system leveraging smart thermostats to detect refrigerant leaks early in retail cold-rooms, enabling proactive maintenance and energy savings.

## Contribution

The paper presents Greina, a scalable leakage detection system that uses ambient data from thermostats to identify refrigerant leaks before manual detection methods.

## Key findings

- Greina detects leaks up to a week early.
- The system was evaluated on 74 retail outlets.
- It improves early leak detection accuracy.

## Abstract

Smart thermostats, with multiple sensory abilities, are becoming pervasive and ubiquitous, in both residential and commercial buildings. By analyzing occupants' behavior, adjusting set temperature automatically, and adapting to temporal and spatial changes in the atmosphere, smart thermostats can maximize both - energy savings and user comfort. In this paper, we study smart thermostats for refrigerant leakage detection. Retail outlets, such as milk-booths and quick service restaurants set up cold-rooms to store perishable items. In each room, a refrigeration unit (akin to air-conditioners) is used to maintain a suitable temperature for the stored products. Often, refrigerant leaks through the coils (or valves) of the refrigeration unit which slowly diminishes the cooling capacity of the refrigeration unit while allowing it to be functional. Such leaks waste significant energy, risk occupants' health, and impact the quality of stored perishable products. While store managers usually fail to sense the early symptoms of such leaks, current techniques to report refrigerant leakage are often not scalable. We propose Greina - to continuously monitor the readily available ambient information from the thermostat and timely report such leaks. We evaluate our approach on 74 outlets of a retail enterprise and results indicate that Greina can report the leakage a week in advance when compared to manual reporting.