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Their product focus is far too limited. Classification of audio is far more valuable than detecting shots. One could detect things like sentiment in a grocery

Their product focus is far too limited. Classification of audio is far more valuable than detecting shots. One could detect things like sentiment in a grocery store nearby a particular product (These prices are too damn high!), reasons your baby is crying, what's that weird sound with your car and who can fix it nearby, virtually any real-time, real-world analytics. It's like google analytics for audio. (Audiolytics, might I suggest). I know it has already been used to try to classify size of cars driving on the freeway. I particularly enjoy this solution for retail locations. How long does someone talk to themselves around a pair of new pants before they buy or walk off and not buy? Is there a correlation between how long a baby screams in a grocery store and how quickly a parent leaves the store without buying something? How about a graph showing me how long my neighbor's dog has been barking each night at 2am? How about that cough? Do other people who have coughs like that end up being diagnosed with <disease_x>?

gnode 9y ago
You're assuming that their implementation is general enough to be applied well to anything other than their target market. They may use an algorithm that's only suitable for differentiating a gunshot from other banging noises, for instance.
- knicholes 9y ago
  I am. But I'm also saying that if this is the case, they should consider making some changes to generalize (or at least increase the breadth of their specialization) if they want to increase their revenue.
  - pininja 9y ago
    Their algorithm and the acoustics of the hardware, as well as the enclosure/power solution, is purpose built for triangulating gunshots sounds from rooftops in a mesh of the devices. Integrating with public safety organizations also took a considerable amount of effort. That is the jist of what I gathered from a former ShotSpotter employee.

gnode 9y ago

You're assuming that their implementation is general enough to be applied well to anything other than their target market. They may use an algorithm that's only suitable for differentiating a gunshot from other banging noises, for instance.

knicholes 9y ago
I am. But I'm also saying that if this is the case, they should consider making some changes to generalize (or at least increase the breadth of their specialization) if they want to increase their revenue.
- pininja 9y ago
  Their algorithm and the acoustics of the hardware, as well as the enclosure/power solution, is purpose built for triangulating gunshots sounds from rooftops in a mesh of the devices. Integrating with public safety organizations also took a considerable amount of effort. That is the jist of what I gathered from a former ShotSpotter employee.