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Can COTS AI Accelerators Survive in Orbit? Radiation, Power, and Fault Handling for Onboard Satellite Inference
Two-thirds of the Earth is under cloud at any moment, so running a neural network on the satellite saves downlink. The real question is not whether a commercial chip is radiation-hard, but whether the system around it detects, contains and recovers from the faults radiation causes.
Srihari Maddula
Oct 2015 min read


LoRaWAN Security Explained: Why "AES-128 Encrypted" Does Not Mean Authenticated End to End, and When You Need Application-Layer AES-CMAC
LoRaWAN is secured with AES-128, but that is a statement about a cipher, not about whether your application can trust a reading. This post shows where the gaps sit and how an eight-byte application-layer AES-CMAC tag closes them.
Srihari Maddula
Oct 2016 min read


Zephyr vs FreeRTOS vs Eclipse ThreadX in 2026: A Decision Framework for Industrial IoT Firmware
Most RTOS comparisons rank scheduler latency and footprint. The factors that decide whether a product line is still maintainable in four years are the support lifecycle and the silicon vendor's software. This framework ranks those first and kernels last.
Srihari Maddula
Oct 2016 min read


RISC-V vs ARM: Which Architecture is Best for AI Hardware?
Edge AI is moving inference down to battery-powered sensors, appliances and small edge nodes. That makes the processor architecture a real design decision, because it affects power, cost, software effort and supply options for years. ARM Cortex-M cores have long been the default in embedded systems. RISC-V, an open instruction set with a modular design, is now a serious alternative for new silicon. This article compares the two for AI workloads: their licensing models, how ea
Srihari Maddula
Mar 156 min read


IoT Architecture: How to Build Scalable SDKs for Global Products?
Reading Time: 25 mins Topic: IoT Architecture & Scalability Bridging the gap between academic projects and industry reality. Global IoT Network The Hook: Why Your MVP SDK Won't Survive Production Building an IoT device that connects to the cloud and sends telemetry is easy. Doing it for one device is a weekend project. Doing it for a hundred devices is a manageable pilot. But what happens when you need to deploy 1,000,000 devices across 50 countries, spanning three major clou
Srihari Maddula
Mar 156 min read


Firmware Reliability: Why Your Code Works on the Desk but Fails in the Field?
Reading Time: 25 mins Topic: Reliability Engineering & Field Debugging Bridging the gap between academic projects and industry reality. It is the universal firmware engineering experience: The code compiles without warnings. The unit tests pass. It runs flawlessly on your dev board for a continuous 48-hour soak test. High-fives are exchanged, the PR is merged, and the fleet is flashed. Three weeks later, the field reports start trickling in. Devices are locking up in Minnesot
Srihari Maddula
Mar 156 min read


Reverse Engineering Firmware: Is Your Code Safe from Hackers?
Reading Time: 25 mins Topic: Embedded AI Bridging the gap between academic projects and industry reality. 1. The Hook: The Illusion of Compiled Safety There is a dangerous myth that persists in the embedded systems industry: “Once the C code is compiled into a binary and flashed onto the microcontroller, our intellectual property is safe.” Nothing could be further from the truth. Every day, competitors, security researchers, and malicious actors are ripping firmware straight
Srihari Maddula
Mar 156 min read


Which RTOS is Best for Real-Time AI and Edge Computing?
Reading Time: 25 mins Topic: RTOS Selection & AI Scheduling Bridging the gap between academic projects and industry reality. Visualizing Circuit board with glowing ai chip. Photo via Unsplash. The Hook: When Determinism Meets the Black Box Imagine a drone navigating a dense forest at 50 km/h. Its flight controller needs hard real-time guarantees—motor updates every 1 millisecond, with sub-microsecond jitter. Simultaneously, a neural network is processing 30fps video feeds to
Srihari Maddula
Mar 156 min read


Product vs Project: Why Engineering Students Fail in Industry?
Reading Time: 25 mins Topic: Engineering Mindset & Productization Bridging the gap between academic projects and industry reality. Indian engineering student soldering a PCB at a cluttered desk The Hook: The Great Indian Engineering Paradox India produces over 1.5 million engineering graduates every year. We have the drive, the mathematical foundation, and the hustle. Yet, ask any hiring manager at a top hardware or embedded systems company, and you'll hear the same frustrati
Srihari Maddula
Mar 157 min read


AI in Firmware: Can LLMs Run on Microcontrollers?
Why on-device AI matters For decades, firmware meant deterministic control: read sensors, drive outputs, manage power within tight limits, and leave the heavy thinking to the cloud. That is changing. Compressed neural networks now run on the microcontrollers that sit next to the sensors. So can a microcontroller run a large language model? Not in the way a cloud LLM runs. Small, specialized models do run well on MCUs today, and combining them is where the useful products are.
Srihari Maddula
Mar 157 min read
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