Leveraging Smart Home-Based Meteorological Sensors and Systems

The adoption of smart home technology continues to increase at an accelerating pace as new technologies are introduced and more competitors enter the market. As the technology moves past the first adopters and into the mainstream of American life, WeatherFlow and other companies are rapidly fielding new weather sensor technologies designed specifically to work with smart home systems. It is easy to see how a smart home could react to changing weather conditions through straightforward "if this then that" rules. For example,

- if outside air temperature goes below X, then tell the HVAC system to turn on, or

- if 24-hour precipitation exceeds Y, then tell the irrigation system to turn off

This pairing of underlying smart home technology with weather sensors provides a tremendous opportunity not only for the consumer to automate tasks in the home, but also for the meteorological community to leverage the meteorological data that is being collected.

Some of these systems are being designed from the start to support the aggregation of their meteorological data, and the potential uses of data from millions of homes are exciting to contemplate. Aggregating all that data (likely thousands of homes in a single metropolitan area) into a single repository not only makes that data more accessible for potential users, it allows quality control and other processes to be run on the data in a standardized manner, yielding an even more useful data set for both non-meteorological and meteorological applications.

For non-meteorological purposes, the aggregated data offers tremendous opportunities across all sectors from energy and agriculture. One of the easiest applications to envision is in the energy sector - if utilities could know street- and home-level temperature data, it would be far easier for them to anticipate and plan for demand surges, helping in generation planning and keeping costs lower for all. Likewise, solar sensors could provide the microscale data necessary for high fidelity solar power generation forecasts. Finally, if hazardous weather events occur (for instance excess precipitation, wind storms, tidal flooding, or intense lightning), better data on the location and intensity of the event will allow utilities to field repair crews more precisely and restores services more quickly.

In the health sector, indoor and outdoor air quality data from smart home sensors could alert caregivers and family members to increased risks for patients with lung ailments like asthma or emphysema, allowing a preventive check in to make sure the patients are aware and are taking steps to mitigate the risk, saving the cost and stress of a preventable emergency room visit.

At the community scale, smart home weather sensors can become an integral part of emerging "smart city" initiatives, affording municipal planners and decision makers far greater awareness of impactful weather conditions throughout their communities. This improved insight enables rapid and flexible responses, whether in the deployment of snow plows, routing of traffic, or the scheduling of community events.

For meteorological purposes, data from smart home sensors can help verify NWP model output and data collected from official sensors, giving NWS personnel more confidence in issuing watches and warnings based on observations. Similarly, alerting systems can be implemented to call NWS personnel's attention to smart home observations that cross certain thresholds, helping those personnel maintain unprecedented local-level situational awareness across areas of responsibility than can cover hundreds of thousands of square miles.

Several efforts will be required to allow this technology to reach its full potential. A first step is the establishment of one or more repositories for the data, where it can easily be accessed en masse by outside users. Private sector repositories like Synoptic Data Corp provide one option, while government repositories like MADIS are another, and future public-private collaborations may also flourish

Once the data is centrally available, new algorithms and techniques are needed to allow quality control and normalization of the data so that it can be assimilated into display systems, decision aids, NWP models, and pre- and post-processing systems. Likewise, improved statistical techniques are needed to account for the increased variability inherent in such large and diverse data sets. Fortunately, many existing Big Data techniques are readily adaptable to these challenges.

Finally, the establishment of some common set of standards and protocols will go a long way to smoothing integration and usage of this data. Professional organizations like AMS can play a crucial role in helping establish and publish these, which will serve to spread critical knowledge and accelerate advances across the sector.

The Weather, Water, and Climate Enterprise is on the threshold of an exciting new era, where new and powerful sources of data become available for the first time. As we get ready to move into that era, early identification, coordination, and planning for the risks and opportunities will be to the benefit of the sector and the citizens it serves.