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    <title>topic Deterministic Sub-Microsecond Safety Layer for Edge AI on Cortex-M (1.18 µs Latency) in MCUXpresso General</title>
    <link>https://community.nxp.com/t5/MCUXpresso-General/Deterministic-Sub-Microsecond-Safety-Layer-for-Edge-AI-on-Cortex/m-p/2345170#M5807</link>
    <description>&lt;P&gt;Hi everyone,&lt;/P&gt;&lt;P&gt;I wanted to share a project designed for mission-critical Edge AI on resource-constrained MCUs like the STM32, LPC, and i.MX series.&lt;/P&gt;&lt;P&gt;MicroSafe-RL is a deterministic C++ safety interceptor that sits between an AI agent and the hardware actuators. It prevents unsafe commands from damaging hardware during Reinforcement Learning exploration or due to sensor drift.&lt;/P&gt;&lt;P&gt;Technical Highlights:&lt;/P&gt;&lt;P&gt;Latency: 1.18 microseconds (WCET) on Cortex-M3 at 72MHz.&lt;/P&gt;&lt;P&gt;Memory: Exactly 20 bytes of RAM, zero dynamic allocation (malloc-free).&lt;/P&gt;&lt;P&gt;Logic: O(1) deterministic execution.&lt;/P&gt;&lt;P&gt;Safety: Uses EMA and MAD statistical profiling to detect hardware drift in real-time.&lt;/P&gt;&lt;P&gt;The project methodology is currently under review at IEEE Transactions on Aerospace and Electronic Systems (Manuscript ID: TAES-2026-1001).&lt;/P&gt;&lt;P&gt;I am looking for feedback from the community on further MISRA-C compliance and hardware-specific optimizations.&lt;/P&gt;&lt;P&gt;GitHub: &lt;A href="https://github.com/Kretski/MicroSafe-RL" target="_blank"&gt;https://github.com/Kretski/MicroSafe-RL&lt;/A&gt;&lt;BR /&gt;Zenodo DOI: 10.5281/zenodo.19019599&lt;/P&gt;</description>
    <pubDate>Sat, 04 Apr 2026 01:01:17 GMT</pubDate>
    <dc:creator>kretski</dc:creator>
    <dc:date>2026-04-04T01:01:17Z</dc:date>
    <item>
      <title>Deterministic Sub-Microsecond Safety Layer for Edge AI on Cortex-M (1.18 µs Latency)</title>
      <link>https://community.nxp.com/t5/MCUXpresso-General/Deterministic-Sub-Microsecond-Safety-Layer-for-Edge-AI-on-Cortex/m-p/2345170#M5807</link>
      <description>&lt;P&gt;Hi everyone,&lt;/P&gt;&lt;P&gt;I wanted to share a project designed for mission-critical Edge AI on resource-constrained MCUs like the STM32, LPC, and i.MX series.&lt;/P&gt;&lt;P&gt;MicroSafe-RL is a deterministic C++ safety interceptor that sits between an AI agent and the hardware actuators. It prevents unsafe commands from damaging hardware during Reinforcement Learning exploration or due to sensor drift.&lt;/P&gt;&lt;P&gt;Technical Highlights:&lt;/P&gt;&lt;P&gt;Latency: 1.18 microseconds (WCET) on Cortex-M3 at 72MHz.&lt;/P&gt;&lt;P&gt;Memory: Exactly 20 bytes of RAM, zero dynamic allocation (malloc-free).&lt;/P&gt;&lt;P&gt;Logic: O(1) deterministic execution.&lt;/P&gt;&lt;P&gt;Safety: Uses EMA and MAD statistical profiling to detect hardware drift in real-time.&lt;/P&gt;&lt;P&gt;The project methodology is currently under review at IEEE Transactions on Aerospace and Electronic Systems (Manuscript ID: TAES-2026-1001).&lt;/P&gt;&lt;P&gt;I am looking for feedback from the community on further MISRA-C compliance and hardware-specific optimizations.&lt;/P&gt;&lt;P&gt;GitHub: &lt;A href="https://github.com/Kretski/MicroSafe-RL" target="_blank"&gt;https://github.com/Kretski/MicroSafe-RL&lt;/A&gt;&lt;BR /&gt;Zenodo DOI: 10.5281/zenodo.19019599&lt;/P&gt;</description>
      <pubDate>Sat, 04 Apr 2026 01:01:17 GMT</pubDate>
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      <dc:creator>kretski</dc:creator>
      <dc:date>2026-04-04T01:01:17Z</dc:date>
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