Technologies That Improve Drone Inspections

I still can’t believe 90% of drone pilots are sleeping on AI. Don’t be that person. Start now: I was recently consulting for a large infrastructure firm. They asked if drone data could be analyzed faster. When I told them I use AI to turn raw footage into reports within hours... They were stunned. This is the problem. The greatest multiplier for drone operations in decades is here Yet most pilots still treat AI like a buzzword, not a tool. This guide will show you exactly where to start: 1️⃣ Start with these 3 high-leverage skills: (You can start applying this in less than 5 minutes) Prompt Engineering ↳ Learn to ask the right questions—context, clarity, and data format matter. Computer Vision Basics ↳ Understanding how AI "sees" drone footage gives you a major edge. Workflow Automation ↳ Link flight > upload > analysis > report → all done with minimal clicks. 2️⃣ Build a lean AI stack: Here’s a sample beginner-friendly setup: ✔️ ChatGPT – Generates client reports, SOPs, and inspection notes ✔️ Roboflow / Scopito – Runs AI image analysis for defects or patterns ✔️ Notion AI – Logs mission insights and generates knowledge base entries Use this combo to build an entire data + delivery system. 3️⃣ Follow these Do’s and Don’ts: ❌ Don’t record gigs and store them on hard drives. ❌ Don’t rely on manual inspection forever. ❌ Don’t chase shiny tools without use cases. ✅ Use AI to augment, not replace, your workflow. ✅ Train tools on your client vertical (e.g. roofing, agri, energy). ✅ Replace time-sucking tasks with automation. 4️⃣ Use this roadmap to get started: Step 1: Audit your current workflow ↳ Automate anything that’s repeatable or admin-heavy. Step 2: Pick 2 AI tools to test ↳ Start with one for image analysis and one for content/output. Step 3: Run one sample project end-to-end ↳ Use real footage, real tools, real client-style output. Step 4: Tweak for your niche ↳ Add annotations, data types, and visual outputs based on industry. Step 5: Build SOPs as you go ↳ Turn wins into repeatable systems for scale. Step 6: Use time saved to go outbound or innovate ↳ More leads. More offerings. More expertise. Most drone operators will regret not learning this early. But you don’t have to be one of them. Start lean. Start smart. Start now. The AI x Drone revolution is already underway. And those who adapt will win more contracts, build authority, and scale faster. #Droneentrpreneur #Droneoperator #Dronecourse #Dronementor #Dronebusiness #Howtolandgigswithdrones

I had an interesting conversation this morning with one of the world's largest wind #turbine companies. Everyone’s chasing drones and robots—but field maintenance still hinges on boots, heat, and hard data. ** Equipment failures account for 42% of unplanned downtime (GE Digital). FLIR Systems thermal cameras paired with rugged phones aren’t just nice-to-haves—they're critical for spotting failures before they shut you down. The real edge? ** Thermographic inspections can identify failing electrical components with 98% accuracy under the right conditions. #VisionAI analyzing that imagery post-capture to flag risks faster than any crew ever could. **Vision-based AI cuts time-to-diagnosis in the field by over 40% compared to manual review. At TechBlocks, we don’t just collect data—we help energy, mining, and utility companies use it to act #smarter and earlier. #AI doesn’t replace field crews. It supercharges them. #FLIR #VisionAI #Techblocks #MaintenanceTech #Utilities #Mining #Energy #RuggedTech

-- Why O&M Managers Need AI and Drone Technology for Solar Farms -- 𝗪𝗛𝗬 𝗔𝗜? 𝗪𝗛𝗬 𝗗𝗥𝗢𝗡𝗘𝗦? Solar farms are massive, complex, and constantly under threat from soiling. Relying on manual inspections or basic monitoring systems can only take you so far. If you’re serious about recovering lost revenue and maximizing efficiency, you need precision insights powered by the best technology. 𝗛𝗘𝗥𝗘’𝗦 𝗪𝗛𝗬 𝗪𝗘 𝗖𝗛𝗢𝗦𝗘 𝗔𝗜 + 𝗗𝗥𝗢𝗡𝗘𝗦: 🚁 Why Drones? 1️⃣ Full Coverage in Hours Manual inspections take days—or even weeks. Drones scan entire arrays in a fraction of the time, delivering faster, more accurate results. 2️⃣ Non-Disruptive Surveys Our drones collect data while your panels stay online, ensuring no downtime or revenue losses during inspections. 3️⃣ High-Resolution Imaging Equipped with thermal cameras, drones detect temperature anomalies (hotspots) caused by soiling. RGB cameras capture visible debris like bird droppings, pollen, and dust, leaving nothing to guesswork. 🤖 Why AI? 1️⃣ Precision Analytics AI doesn’t just see soiling—it measures its impact. We calculate energy losses down to the panel level and predict how much revenue you’ll recover by acting. 2️⃣ Pattern Detection AI identifies trends in soiling buildup over time, helping you understand your site’s unique challenges and prepare for them. 3️⃣ Tailored Cleaning Triggers Instead of static cleaning schedules, AI tells you when soiling has reached a critical point—ensuring cleaning is done only when and where it’s truly needed. 𝗧𝗛𝗘 𝗗𝗜𝗙𝗙𝗘𝗥𝗘𝗡𝗖𝗘 𝗧𝗛𝗜𝗦 𝗠𝗔𝗞𝗘𝗦 𝗧𝗢 𝗢&𝗠 𝗠𝗔𝗡𝗔𝗚𝗘𝗥𝗦 ↬ Fewer Unknowns: Data-driven insights eliminate guesswork, so you can make informed decisions. ↬ Higher ROI: Cleaning at the right time maximizes energy recovery and justifies every maintenance dollar. ↬ Confidence for Asset Owners: Detailed reports show the ROI of your actions, building trust and transparency. Ha - you know how they say "Better Ingredients...Better Pizza...Papa Johns"? 𝗖𝗟𝗘𝗔𝗡𝗘𝗥 𝗗𝗔𝗧𝗔. 𝗕𝗘𝗧𝗧𝗘𝗥 𝗗𝗘𝗖𝗜𝗦𝗜𝗢𝗡𝗦. Solar Survey Ai.

A small business called Near Earth Autonomy developed a time-saving solution using drones for pre-flight checks of commercial airliners through a NASA Small Business Innovation Research (SBIR) program and a partnership with The Boeing Company. Before commercial airliners are deemed safe to fly before each trip, a pre-flight inspection must be completed. This process can take up to four hours, and can involve workers climbing around the plane to check for any issues, which can sometimes result in safety mishaps as well as diagnosis errors. With NASA and Boeing funding to bolster commercial readiness, Near Earth Autonomy developed a drone-enabled solution, under their business unit Proxim, that can fly around a commercial airliner and gather inspection data in less than 30 minutes. The drone can autonomously fly around an aircraft to complete the inspection by following a computer-programmed task card based on the Federal Aviation Administration’s rules for commercial aircraft inspection. The card shows the flight path the drone’s software needs to take, enabling aircraft workers with a new tool to increase safety and efficiency. “NASA has worked with Near Earth Autonomy on autonomous inspection challenges in multiple domains,” says Danette Allen, NASA senior leader for autonomous systems. “We are excited to see this technology spin out to industry to increase efficiencies, safety, and accuracy of the aircraft inspection process for overall public benefit.” The photos collected from the drone are shared and analyzed remotely, which allows experts in the airline maintenance field to support repair decisions faster from any location. New images can be compared to old images to look for cracks, popped rivets, leaks, and other common issues. The user can ask the system to create alerts if an area needs to be inspected again or fails an inspection. Near Earth Autonomy estimates that using drones for aircraft inspection can save the airline industry an average of $10,000 per hour of lost earnings during unplanned time on the ground. Over the last six years, Near Earth Autonomy completed several rounds of test flights with their drone system on Boeing aircraft used by American Airlines and Emirates Airlines. NASA’s Small Business Innovation Research / Small Business Technology Transfer program, managed by the agency’s Space Technology Mission Directorate, aims to bolster American ingenuity by supporting innovative ideas put forth by small businesses to fulfill NASA and industry needs. These research needs are described in annual SBIR solicitations and target technologies that have significant potential for successful commercialization. #SBIR #NASA #Boeing A Boeing 777-300ER aircraft is being inspected by one of Near Earth Autonomy’s drones Feb. 2, 2024, at an Emirates Airlines facility in Dubai, United Arab Emirates. (Near Earth Autonomy)

Drone ‘powered’ energy Technology is transforming the way power utility companies go about their businesses. From using drones for perilous inspections to the use of sensors and Asset monitoring solutions to stabilize large grids rapid changes have been witnessed in the sector. But what advantages do incorporating drone and sensor technologies bring into the equation? • Using drones’ professionals can now operate at a safe distance instead of engaging with high-voltage transmissions which previously electrocuted 25 workers annually. • The service efficiency goes up since drones can not only cover a larger precinct but also do it faster while reducing the costs by 30-50% • Drones are capable of delivering data such as HD and thermal imaging, LIDAR in real-time helping pace up the decision-making process and also foresee and prevent major incidents from happening. This data can further optimize the functioning of the system when used in synergy with Asset Monitoring Solutions. • Using the technology for continuous oversight of assets thereby ensuring the health and safety of the infrastructure while providing real-time access • Digital data eases the conundrum of how to record and process data and subsequently ensure compliance reporting • This data can then be analyzed to predict and forecast events based on historical trends  • Incorporation of the latest technology like GFMs to further enhance grid stability. An incident from April 2023 showed how GFMs potentially saved $10 million when an oil-powered generator went offline highlighting the immense potential. What is your opinion, are such digital solutions the way forward for greener grids? #innovation #technology #energy #sustainability #electricalengineering ASEC ENGINEERS - Engineering your success, delivering precision and innovation in every project since 1991.