Internet of Things (IoT) is at the top of its hype cycle curve, the peak of inflated expectations. Many companies are working on an IoT solution or have an IoT solution. Over the past several months, in talking to prospects, investors, and co-entrepreneurs,there seems to be a disconnect on the requirements for an effective IoT solution, especially regarding the importance of sensor data in particular the data’s granularity and velocity needed for successful cloud analytics.
This series discusses the critical nuances of an IoT solution, the slope of enlightenment, that delivers on the promise of a more productive, cost effective or new business process or opportunities. The post starts at a very fundamental level:
How is IoT Different Than Smart Connected Devices?
Fitbit/JawBone products are well known wearable devices that are used by consumers to exercise more, track their sleep patterns, and aid in tracking an individuals health over time.
But not immediately apparent there is something else occurring: You are no longer the only source of data about yourself. Fitbit/Jawbone is automatically collecting over time and anonymously sending to the cloud data that reflects more accurately your environment.
For example as mentioned here, the aggregated individual sleep disturbance over time was able to recognize the recent Napa, Calif. earthquake. Seismic sensors can very quickly tell that an earthquake had occurred, but what was not apparent was the human impact, and the resulting human consequences of the earthquake, that FitBit should be able to capture from their aggregated data. It is not far fetched that emergency services can predict and allocate resources by looking at individual data points generated by these wearable things in future.
A single wearable device is simply a connected device, nothing more. However, a connected device which is so focused on an individual suddenly became part of bigger intelligence producing infrastructure. And that is IoT: Intelligence of Things.
Though relevant technologies has been available for long time, IoT is made possible now because of cheaper sensors and cloud scalable big data analytics infrastructure.
IoT solution requires analytics as a critical component, and analytics requires copious amount of data to detect patterns which inevitably escape human observation. The data’s source and context drive statistical valuable results. IoT is unique in that the copious amounts of sensor data are well defined and easily interpreted. If we reduce the data to analytics, outcome of analytics may not be complete, hence resulting in lost opportunities.
Teevr Data allows IoT Solution designers to not compromise on the amount of data and
sampling rate that they want for full intelligence from their sensor data. Teevr unlocks previouslyin-feasibleanalytics by delivering data to your Analytics at the speed of data generationrather than delayed, filtered or dropped data.