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| Source: Ambi Labs. |
Overall, 72% of respondents in the region identified with at least one AC usage issue, such as finding the room too warm, too cool, too dry or too humid at times.
Ambi Labs' research indicates that these difficulties are largely due to the outdated design of existing AC remotes. "Current remote controls encourage the user to focus on power and temperature buttons, so it is unsurprising that many users engage in inefficient on/off control behaviour - they switch on their ACs when they are hot, and switch them off when it gets too cold. The resulting 'yo yo-ing' in temperature, as some of our research participants called it, is both uncomfortable and a waste of energy. They have also complained about needing to adjust their ACs as much as every 30 minutes," said Julian Lee, Founder and CEO of Ambi Labs.
Ambi Climate is designed to manage the AC while minimising energy consumption with machine learning techniques. According to the company, the product can predict conditions in the area, remember user preferences, local weather patterns and the building's heating and cooling profile.
"Recently, several learning thermostats and AC controllers have appeared on the market, but most of these predict the schedule of the user, i.e. when they are home and when they are out, and automatically switch the AC on and off to match. Our research shows that this isn't a challenge in Asia - users typically switch on their ACs when they need them, and do not need help in this regard," said Lee.
The funding campaign ends in August.
