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Apple removed ICEBlock reportedly after direct pressure from Department of Justice officials. “I am incredibly disappointed by Apple's actions today. Capitulating to an authoritarian regime is never the right move,” the developer said.

Apple removed ICEBlock reportedly after direct pressure from Department of Justice officials. “I am incredibly disappointed by Applex27;s actions today. Capitulating to an authoritarian regime is never the right move,” the developer said.#News


ICEBlock Owner After Apple Removes App: ‘We Are Determined to Fight This’


The developer of ICEBlock, an app that lets people crowdsource sightings of ICE officials, has said he is determined to fight back after Apple removed the app from its App Store on Thursday. The removal came after pressure from Department of Justice officials acting at the direction of Attorney General Pam Bondi, according to Fox which first reported the removal. Apple told 404 Media it has removed other similar apps too.

“I am incredibly disappointed by Apple's actions today. Capitulating to an authoritarian regime is never the right move,” Joshua Aaron told 404 Media. “ICEBlock is no different from crowd sourcing speed traps, which every notable mapping application, including Apple's own Maps app, implements as part of its core services. This is protected speech under the first amendment of the United States Constitution.”

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Do you know anything else about this removal? Do you work at Apple or ICE? I would love to hear from you. Using a non-work device, you can message me securely on Signal at joseph.404 or send me an email at joseph@404media.co.

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Implementing a Kalman Filter in PostgreSQL to Smooth GPS Data


Usually databases are treated primarily as fairly dumb data storage systems, but they can be capable of much more. Case in point the PostgreSQL database and its – Ada-based – PL/pgSQL programming language, which allows you to perform significantly more complex operations than would be realistically possible with raw SQL. Case in point the implementation of a Kalman Filter by the folk over at Traconiq, which thus removes the necessity for an external filtering pipeline.

Using a Kalman Filter is highly desirable when you’re doing something like vehicle tracking using both dead-reckoning and GPS coordinates, as it filters out noise that can be the result of e.g. GPS reception issues. As noted in the article, transferring state from one row to the next requires a bit of lateral thinking, but is doable with some creative SQL usage. As PL/pgSQL is very similar to Oracle’s PL/SQL, this same code should work there too without too much porting required.

The code for the different implementations and associated benchmarks can be found on GitHub, though the benchmark results make it abundantly clear that the most efficient approach is to run an offline aggregate processing routine. This coincides with the other batch processing tasks that are typically performed by a database server to e.g. optimize storage, so this isn’t entirely unsurprising.


hackaday.com/2025/10/02/implem…