Jun 112019
 

According to information released in response to a public records request, the Northern California Regional Intelligence Center collected more than 79.2 million license plate reader records from 32 local law enforcement agencies from June 2018 to May 2019.

Piedmont, a city with about 11,000 people, sent the most data to NCRIC, with more than 22.4 million license plate reader records, which include license plate numbers and photographs of vehicles and their surroundings. Piedmont has more than 30 stationary license plate readers that capture nearly all traffic coming into and out of Piedmont.

In calendar year 2018, Piedmont collected 21.6 million records from its license plate readers and reported 8,120 hits, when a record from a license plate reader matched a list of license plates that includes stolen vehicles, stolen license plates, wanted persons, etc. Using that information, 99.96% of the data collected by Piedmont’s license plate readers is from people who are not suspected of are charged with any crime. That closely matches a similar analysis in 2014 that showed 99.97% of the data collected from Piedmont’s license plate readers did not generate a hit.

Fremont, a city with about 230,000 people, sent 17.7 million records to NCRIC and Vallejo, a city of 120,000 people, sent 15.8 million records to NCRIC.

Other agencies sending more than a million records to the NCRIC each year include the Central Marin Police Authority (Larkspur, San Anselmo and Corte Madera), Daly City, San Francisco, Modesto, Alameda County Sheriff, San Leandro, and South San Francisco.

Other law enforcement agencies use license plate readers from Vigilant Solutions, a private company that collects data from law enforcement agencies and private companies. Data from 2017 indicates that Bay Area agencies in Danville sent 33.4 million license plate records to Vigilant, Pittsburg sent 31.4 million records, Brentwood sent 12.9 million records, and Alameda and Novato each sent 1.6 million records.

Sources:

Sep 072015
 

In 2013, the City of Piedmont, California, spent almost $600,000 to purchase 39 license plate readers covering most of its border with Oakland. With a population of less than 11,000 people, these 39 license plate readers collect photographs and license plates from more than 1,000,000 vehicles every month. The City of Piedmont sends this data to a regional license plate data warehouse at the Northern California Regional Intelligence Center (NCRIC), where it is stored for one year, even if the data does not generate a “hit” as a stolen vehicle, being registered to a wanted individual, etc.

The City of Oakland, with a population of more than 400,000 people, took three years to gather 4.6 million license plate reads and photographs (see We know where you’ve been: Ars acquires 4.6M license plate scans from the cops). In Piedmont, that same amount of data would be collected in less than 5 months.

Using the information gathered by Oakland’s license plate readers, Ars Technica was able to determine where Oakland City Councilmember Dan Kalb worked and lived with his vehicle captured just 51 times between May 2012 and May 2014. Data from license plate readers could reveal churchgoing habits, whether you visit a medical marijuana dispensary or a health clinic, and whether you spend the night with someone other than your spouse.

Until June 2014, NCRIC generated a report on total license plate reads submitted to it by each agency. Combined with the number of hits reported by the Piedmont Police Department, this data shows that 99.97% of the data collected by Piedmont’s license plate readers is useless – it is data collected about people who are not charged with or suspected of any crime. For example, in April 2014, Piedmont submitted 1,420,244 license plate reads and photographs to NCRIC and only generated 400 hits. That is a hit rate of 0.00028 or 0.028 percent. Below is a table showing this information from December 2013 to June 2014:

Month Total reads Hits Percentage
12/2013 1272871 532 0.042
1/2014 1201196 374 0.031
2/2014 1025771 276 0.027
3/2014 1189422 323 0.027
4/2014 1420244 400 0.028
5/2014 1462313 465 0.032
6/2014 1213121 391 0.032

 

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