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Smart Sensors & Digital Wallets: How IoT Devices Are Becoming Financial Endpoints

Remember when sensors were just simple devices that could detect temperature or motion? Today, these smart devices are turning into tiny banks capable of making and receiving payments all by themselves, even tracking cryptocurrency stats like the Aixbt price in real-time. Let's explore how the IoT is changing the way we think about financial transactions.

Meta's Big Bet on AI Wearables

Meta is making a massive push into AI wearables, with at least six new devices launching in 2025. But here’s the catch—this wasn’t originally about AI. Meta built its hardware for the metaverse, only to find itself at the center of the AI revolution. With over 1 million Ray-Ban smart glasses already sold (and a goal of 5 million in 2025), it’s clear there’s demand. But can Meta actually scale this initiative from within, or will they lean on brand partnerships like Oakley to expand?

Integrating IoT Devices with Feedlot Management Systems for Enhanced Data Collection

The agricultural industry is undergoing a technological revolution, and the livestock sector is no exception. With increasing global demand for meat production, feedlot operations must maximize efficiency, ensure animal welfare, and optimize resource utilization. The integration of Internet of Things (IoT) devices with feedlot management systems offers a groundbreaking approach to data collection, providing real-time insights and improving decision-making processes. This article explores how IoT enhances feedlot management, the benefits of integration, challenges, and future prospects.

The One Thing Most Engineers Don't Understand (But Should)

How can engineering teams have a bigger impact on the bottom line? By thinking beyond code. Most engineers love to build and solve problems. But in a business, building for the sake of building isn’t enough. Even the cleanest code is just an expensive distraction if it doesn’t move the needle.

How IoT Brands Waste Money

Some IoT companies are making money; others are leaking it. Margins in IoT are already tight, but many brands are losing cash in ways that are completely preventable. RMAs, bloated customer support costs, churn, and on-site technician visits all add up. Too many companies default to replacing hardware instead of fixing the code. Without OTA updates and remote diagnostics, budgets get drained by unnecessary shipping and support costs.

Linux Coredumps (Part 1) Introduction

One of the core features of the Memfault Linux SDK is the ability to capture and analyze crashes. Since the inception of the SDK, we’ve been slowly expanding our crash capture and analysis capabilities. Starting from the standard ELF coredump, we’ve added support for capturing only the stack memory and even capturing just the stack trace with no registers and locals present.

From Detection to Prevention: Leveraging InfluxDB for Cybersecurity and IoT Threat Mitigation

Cybersecurity in the Industrial Internet of Things (IIoT) is often overlooked despite powering critical infrastructure such as energy grids, telecom networks, factories, robotics, and aerospace, all of which are prime targets for cyberattacks and data breaches. A single breach can disrupt essential services or expose sensitive data. So, how do we stay ahead of bad actors and proactively defend these systems?

AI in Embedded Systems: A Black Box You Must Learn To Control

AI isn’t predictable, it adapts, making embedded engineering even more complex. A model that works in the lab might fail in the real world. So, how do successful teams deploy AI at the edge? A/B test models in the field—controlled environments aren't enough. Collect real-world performance data—observability tools are key. AI deployment isn’t a one-and-done process. It requires constant iteration and real-world validation.

Fitbit's $12M Lesson: The Cost of Poor Monitoring

Fitbit was just fined $12M after Ionic smartwatches overheated and burned users. The issue? Lithium-ion batteries—powerful, but risky without proper safeguards. The best teams know you can’t catch every failure before launch. That’s why real-time monitoring is critical: Over-temperature protection isn’t enough without tracking trends. Live monitoring helps catch small issues before they become safety risks. Think about it: What if an e-bike motor overheats mid-ride? Or a smart oven malfunctions and starts a fire? Without monitoring, you’re gambling with user safety.

AI in Embedded Systems: A Black Box You Must Control

AI isn’t predictable, it adapts, making embedded engineering even more complex. A model that works in the lab might fail in the real world. So, how do successful teams deploy AI at the edge? A/B test models in the field—controlled environments aren't enough. Collect real-world performance data—observability tools are key. AI deployment isn’t a one-and-done process. It requires constant iteration and real-world validation.