Silicon Sheriffs: What Chatrie Means for Enhanced Vehicle Surveillance

By John Ellis¹

Editor’s Note: This is the third article in our series on Chatrie v. United States. The first explained the Supreme Court’s holding that obtaining Google Location History through a geofence warrant is a Fourth Amendment search. The second applied that reasoning to cellular area searches. This article turns to roadside camera networks.

“Automated license plate reader” is an increasingly misleading term. Modern cameras do not merely read license plates. They photograph vehicles, record where and when they appear, classify their make, model, color, and distinguishing features, aggregate records across multiple jurisdictions, and feed searchable systems that can reconstruct movements and infer associations. The license plate is only the index to the conglomerated data.

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Same Fence, Different Tower: What Chatrie Means for Cellular Area Searches

By John Ellis[1]

Editor’s Note: This article is a companion to our earlier primer on Chatrie v. United States, which explained the Supreme Court’s June 29, 2026, holding that obtaining a person’s Google Location History through a geofence warrant is a Fourth Amendment search. See The Fourth Amendment Catches Up to Digital Dragnets.

Here we turn from Google to the wireless carriers. Our thesis is simple: because Chatrie forecloses the government’s no-search and third-party defenses to carrier location data, the real fight over cellular area searches now moves to the warrant itself—its probable cause, particularity, and execution, and whether good faith can save a defective one. Google has started storing Location History on users’ phones instead of its own servers, which makes the classic Google geofence warrant harder to run. The technique law enforcement is turning to instead is the cellular area search, in which a search warrant requires a wireless carrier to determine which devices were within a specific geographic area during a certain time-period. This piece explains what those searches are, how their Timing Advance and proprietary location-estimate data compare to the records in Carpenter and Chatrie, and why Chatrie‘s reasoning reaches them with at least equal force. Because these searches already proceed by warrant, Chatrie‘s significance is not that it requires one; it is that it puts the warrant’s probable cause, particularity, and execution squarely in play. Defenders and CJA practitioners handling carrier location evidence should read this alongside the Chatrie primer and assess the implications now.

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The Fourth Amendment Catches Up to Digital Dragnets: A Primer for Suppression Litigation After the Supreme Court’s Landmark Ruling in Chatrie

By John Ellis [1]


Editor’s Note: Okello Chatrie’s case began as a 2019 Virginia credit-union robbery investigation and reached the Supreme Court as a major test of geofence warrants. On June 29, 2026, in Chatrie v. United States, No. 25-112, a five-Justice opinion authored by Justice Kagan held that police conduct a Fourth Amendment search when they obtain Google Location History through a geofence warrant. Justice Gorsuch concurred in the judgment, giving the threshold search holding six votes, though only five Justices joined the Court’s Katz/Carpenter rationale. The decision settles the threshold search question that divided lower courts, but leaves probable cause, particularity, reasonableness, and good faith for the Fourth Circuit on remand. Defenders and CJA practitioners litigating digital location evidence should assess the implications immediately.

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dtSearch Guide – Part VII: Refine Your Search Results with “Search Within These Results”

By Tisha DavisDerek Ametam and Joe Wanzala 

This is the seventh installment in our series on dtSearch.  In this installment, we will explore how to leverage dtSearch’s ‘Search Within these Results’ feature to “drill down” or refine your search results.  You can find the previous installments here:  Part 1Part 2Part 3Part 4Part 5 and Part 6

In today’s litigation, we often get voluminous amounts of discovery on a rolling basis.  Linear review of those discovery productions can result in going down multiple rabbit holes before we find the relevant, useful information. 

As we mentioned in earlier installments, dtSearch is a good search and retrieval tool built to help users quickly find relevant information in massive datasets.  You may have an idea on what names, keywords, terms, or phrases you want to search for.  You may think that you need to run each search separately.  This approach, while good-intentioned, could lead to you spending extra time reviewing duplicative results.  This can be especially time-consuming in cases with lots of data.

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dtSearch Guide – Part VI: Exploring Your Discovery with the Search Features Panel in dtSearch

By Tisha DavisDerek Ametam and Joe Wanzala 

This is the sixth installment in our series on dtSearch. In this installment, we’ll continue to explore how to actually search your discovery data and make the most of dtSearch’s powerful search capabilities. You can find the previous installments here: Part 1Part 2Part 3Part 4 and Part 5

In this installment, we will explore how to leverage dtSearch’s advanced Search features to further refine and expand your searches. These powerful options—such as fuzzy searching, synonym searching, stemming, phonic searching, and more—allow you to handle common real-world challenges like misspellings, OCR errors, varied terminology, and conceptual relationships.

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