Paige Leuschner for SmartCitiesDive:  A phrase hyped around a variety of industries, data analytics has futuristic and hopeful possibilities for efficiency gains and optimization. Analytics involves using algorithms to identify patterns in data that can provide actionable insights, and can be used to improve city parking and reduce traffic congestion, increase building energy efficiency, foster safer streets, reduce energy consumption in homes, and generally create smarter cities and businesses. As a node in broader smart cities, homes can utilize analytics to enable more advanced functionality that can then morph them into dynamic grid assets in the Energy Cloud. The concept of a smart, connected home continues to gain traction, and stakeholders are increasingly exploring analytics solutions to push this vision forward.

How it works

The storage, analysis and delivery of smart home data to a user platform involves multiple technologies and processes, and are depicted in the figure below. Each step of the process can involve data analytics — from local analytics (a technology trend known as fog computing) to analytics in a server offsite (a technology trend known as cloud-based analytics) — and this depends on the type of data a device is transmitting. For example, some energy monitors, such as Smappee, locally employ analytics because the device produces copious amounts of granular data, and it does not make sense to send all of this information to the cloud.

As smart home technology adoption grows and more data is produced, companies should experiment with employing analytics along different parts of the technology stack to avoid major bandwidth and storage issues that require expensive investments in IT infrastructure.  Full Article: