At Stream It, our customers expect and depend on precise, real-time analytics from their transit vehicles.
Stream It provides a broad array of real-time analytics from our neural surveillance cameras and other sensors on buses and trains. Our focus is the Internet of Recognition - the use of machine vision and artificial intelligence to see the unseeable and intelligently transform what we see into analytics and real-time notifications. The data we collect is used for a variety of purposes including improved public safety, added security, and customer convenience.
Using our advanced onboard AI-enabled Stream It Edge appliance, we can monitor in real-time the bus driver's line of sight, posture, and behaviors to look for tell-tale signs of drowsiness. Our SlipStream network captures and evaluates observed events in milliseconds making it possible to alert the driver and dispatch operators - and all in just under a second.
Our analytics and tracking data are stored in ElasticSearch where - again - our customers are able to glean details about their operations in split-second queries. Searching for the details about a nefarious person, for instance, can be accomplished within seconds of an observed AI event that just occurred on a public bus.
This real-time expectation extends to our support portal as customers sometime want to view current analytics in an easy-to-access environment.
Imagine a bus driver has reported problems with her vehicle to the dispatch operator. The brakes don’t seem right and the bus isn’t stopping as easily as it should.
Using an integration between ElasticSearch and our FreshService customer portal we are able to display analytics about the bus in real-time. Dispatch and maintenance people can monitor vehicle analytics of the bus while it is in service.
When I evaluate SaaS products, I tend to seek out attributes and instances where the designers have thought about unanticipated use cases. A good example is an ability to leverage open [HTML] standards when publishing content in the support portal.
FreshService provides an open and architecturally sound method of integrating data and visuals into support content by exposing the underlying HTML plane of solution pages. While it’s great that you can fully customize your customer-facing portal design and layout, FreshService architects went a step further by opening up the content to access at an HTML level. This makes it possible to leverage HTML5 features to embed videos and IFrames for example. In our case, we need to embed data visualizations. Dropping in an <IFrame> tag is simple work.
Elastic Search provides a sharing architecture that is equally well-crafted to meet our real-time analytics requirements.
Using the share feature in Elastic Search, we can easily embed data visuals and configure them for real-time refresh rates that meet our customer's viewing requirements. Elastic Search’s share feature includes pre-fabricated iframe code that can be used straight-away for displaying data visualizations.
The combination of FreshService, Elastic Search, and real-time data provides a wonderful support capability that our customers truly appreciate.
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