Various horizontal and vertical approaches exist for entering the IoT market. The debate about IoT market strategies will continue because of the bold projections for the IoT market. Unfortunately, hype leads to myth, and myth leads to confusion.
Moving forward means taking a step back to look for clues about how the IoT market could evolve. Let’s dive into a practical example from the Smart Home market to see how the future of HVAC systems is intertwined with AI and IoT.
Early HVAC Innovations
HVAC controls have been a key focus of the Smart Home market. As recently as 2017, 41 percent of U.S. homes had a programmable thermostat, but less than 1/3 of those homes actually programmed it.
HVAC controls have existed for a while. The first thermostat was patented in 1883!
What’s Changed in 135 Years?
As the story goes, hot air furnaces operating in the basement of the building heated classrooms. School custodians controlled the heat through hand-operated dampers based on periodic assessments of the classroom temperature. The teacher, Warren Johnson, sought to eliminate these classroom disruptions and developed the technology to maintain a constant temperature in the classroom. Genius! He subsequently launched a company known today as Johnson Controls.
The technology for automated room temperature control has existed for 135 years! Has much changed in the basic temperature control architecture during that span of time? Sadly, we could say, not really. Even today, data from a single temperature sensor controls the actuation of most HVAC units in homes.
“Smart” thermostats are a very recent innovation, at least within the 135-year history of HVAC. What makes a thermostat “smart”? Programmable schedules and vacation modes? No. Internet connectivity? Not enough. In one definition, “smart” thermostats must have more than two-way communication and they must include “algorithms.”
A recent example, GLAS by Johnson Controls, includes multiple onboard sensors that allow the device to adapt to your schedule. GLAS even supports voice commands for user comfort controls. Interestingly, a third-party, cloud-based voice assistant (Amazon Alexa) can pass control commands such as “Set the thermostat to X degrees” to GLAS.
This third-party control interface represents a new thermostat architecture that decouples the hardware HVAC unit signaling from the software “algorithms.” As has been known for 135 years, an on-site thermostat device can physically transmit a signal that changes the operation of the HVAC unit. The software “algorithms,” on the other hand, can exist off-site in a separate, cloud environment.
AI and IoT Intersect in HVAC
The decoupling of the “algorithms” from the on-site thermostat control allows us to visualize the interplay between AI and IoT.
Assume, for example, that a thermostat (be it basic or “smart”) exists in a home. Regardless of the actual thermostat’s capabilities, a cloud-based AI analytics engine can implement HVAC “algorithms” in a third-party application layer.
IoT Driving a 3rd-Party Application Layer
The AI analytics engine would need data to run. Where would it get the data? IoT, of course. IoT sensors can be installed throughout a home to collect data from every room—not just the room with the thermostat. The IoT sensors transmit data to the cloud for processing by the AI analytics engine. HVAC commands produced by the AI algorithms and delivered to the thermostat would ultimately optimize and control the HVAC unit. Certainly, the decoupling of the sensors from the thermostat control unit would represent a significant change from the automated room temperature control invented 135 years ago.
IoT + AI = The Future
Let’s take this inquiry further. Would the existence of IoT sensors lead to the development of better AI analytics engines? Or, would the existence of AI analytics engines lead to the installation of more IoT sensors?
Many companies have already placed bets on this question. Certainly, the investment community has weighed in as well. It isn’t quite a chicken and an egg problem, but it does reveal the interplay between AI and IoT.
AI is the domain of subject matter experts (SMEs). Spread across countless industries, these SMEs already have existing “algorithms.” They need data, lots of it. If this theory prevails, then AI may certainly lead the way for IoT in terms of demand for data.
Consider the flip side. If widespread IoT deployments were a reality, then vast stores of data would exist. Algorithms could quickly emerge to leverage that data. Under this theory, the existence of IoT data would lead the way for AI. IoT and AI represent twin forces either way.