A large problem in high crime neighbourhoods is that the police relies on witnesses to report gun violence, but less than 25 percent of the actual gun violence is reported (Faggella 2018). How can the authorities even fight gun violence when it is not reported? ShotSpotter found an interesting solution for this problem.
ShotSpotter is a system that detects gunfire by using acoustic sensors and cameras. The system is capable to identify gunfire and alert the authorities, even when no one calls the emergency services. ShotSpotter claims that they alert the authorities faster and give more detailed descriptions about incidents so that the authorities can respond more efficiently (Shotspotter 2011).
The sound sensors and surveillance cameras are strategically installed within neighbourhoods that are dealing with high crime rates. When a gunshot is fired, the sensors will detect the sound and the cameras will turn towards the direction of that sound. Analysts will confirm if it is the sound of a gunshot and a machine learning algorithm will simultaneously compare the sounds picked up by different sensors. This algorithm then determines the exact location of the gunshot and alerts the authorities. The authorities can log in onto the system, access the surveillance footage and examine the crime scene (Weller 2017; Faggella 2018).
SpotShotter is helping the authorities to reduce their response time since they are immediately alerted after the incident. It is also increasing the number of arrests because the authorities can immediately check the surveillance footage and identify offenders. Furthermore, it helps the authorities to find more gunshot victims. If a victim is alone, the authorities are still alerted even if there are no witnesses (ShotSpotter 2018; Faggella 2018).
In my opinion, this could improve the fight against gun violence. The authorities will no longer only depend on subjective human reports, but can rely on the objective data that this system provides for them.
Sources:
Faggella, D., 2018, AI for Crime Prevention and Detection – Current Applications. Available at: https://www.techemergence.com/ai-crime-prevention-5-current-applications/ [Accessed: 1 October 2018]
Shotspotter, 2011, SST – ShotSpotter Overview. [online video] Available at: https://www.youtube.com/watch?v=VBxqUBA_br8 [Accessed 1 October 2018]
Weller, C., 27 June 2017, There’s a secret technology in 90 US cities that listens for gunfire 24/7. Available at: https://www.businessinsider.nl/how-shotspotter-works-microphones-detecting-gunshots-2017-6/?international=true&r=US [Accessed 2 October 2018]
ShotSpotter, 2018, Results. Available at https://www.shotspotter.com/results/ [Accessed 2 October 2018]
Hi Francis,
Thank you for your interesting article.
I agree with you that this technology helps to identify gun violence, but I read an article concerning the results that ShotSpotter had and thought it would be interesting to share with you.
This article states that 30 to 70 percent of the time, the police are not able to find any evidence of gunshots on the reported locations. This means that the authorities lose meaningful time by reacting on the reports and that the technology still needs a lot of improvements. Furthermore, because it is still quite an investment and the accuracy sometimes is questionable too, in this moment in time, a lot of cities prefer to use the money to hire additional police officers and fund more traditional technologies as surveillance cameras.
I think the idea behind the technology is a big step forward, and even though it is not perfect yet, every life saved by this technology is worth the investment.
Drange, M. (2018). ShotSpotter Alerts Police To Lots Of Gunfire, But Produces Few Tangible Results. [online] Forbes.com. Available at: https://www.forbes.com/sites/mattdrange/2016/11/17/shotspotter-alerts-police-to-lots-of-gunfire-but-produces-few-tangible-results/?ss=china-billionaires#58a3d0d1229e [Accessed 4 Oct. 2018].