Real-Time Tracking Systems

🚨 Exclusive: Russian Navy Escorts Shadow Fleet Tankers Through English Channel A major step in sanctions evasion. For the first time, we now have confirmation of Russian naval escorts accompanying unflagged, sanctioned tankers through European waters. 🎥 The video below shows AIS movements since 16 June — revealing how two shadow fleet tankers and a Russian warship coordinated to enter the English Channel together. Their movements suggest deliberate timing to allow all three vessels to transit simultaneously, en route to load oil in Russia. - BOIKIY, a Steregushchy-class Russian Navy corvette. - SELVA (aka NOSTOS/NAXOS) — UK sanctioned, transmitting AIS as Panama-flagged, but listed as flag unknown in the IMO database. (UPDATE: as of 22 June 17:00 UTC Palau flagged) - SIERRA (aka SUVOROVSKY PROSPECT) — UK & EU sanctioned, falsely flagged to Malawi, confirmed by Lloyd's List. 🇫🇮 Finland’s Defence Minister warned these escorts were coming, calling them “unprecedented.” These new actions confirm what many suspected: following Estonia’s boardings and growing scrutiny from EU states, Russia is now openly protecting the shadow fleet with naval force. 🛰️ Huge credit to OSINT experts on Bluesky — especially Christian Panton 🚀 — for first identifying the vessels. At Starboard Maritime Intelligence, we’re continuing to track these tankers and flag evolving behaviour. This isn’t a grey zone anymore. It’s a test of whether enforcement and international resolve are ready for what comes next. #ShadowFleet #RussianNavy #SanctionsEvasion #MaritimeSecurity #EnglishChannel #BalticSea #MDA #OSINT #AIS #Starboard

💡#China is deploying #AI-#powered #robots inside #grain #warehouses to handle some of the most dangerous tasks humans used to do. 🤖🌾 💡Grain #storage #facilities are #high-#risk #environments. They are filled with dust, extreme heat, low oxygen levels, and unstable #grain #piles. Long exposure can lead to serious #health #issues and #accidents. 💡These Al robots are designed to enter the warehouses, #inspect grain piles, #monitor #temperature and #humidity, #detect potential #spoilage or #hazards, and move through spaces that are unsafe for people. Using #sensors, #cameras, and #autonomous #navigation, they can #work #continuously without putting #human #lives at risk. 💡The result is higher #efficiency, better grain #preservation, and improved #safety #standards. Instead of sending workers into hazardous conditions, #operators can monitor everything #remotely while robots handle the risky part. 📌This is not about replacing humans everywhere. It's about removing people from dangerous environments and letting machines do what they're better suited for.

𝗔𝗻𝗸𝗶𝘁𝗮: You know 𝗣𝗼𝗼𝗷𝗮, last Monday our new data pipeline was live in cloud and it failed terribly. Literally had an exhaustive week fixing the critical issues. 𝗣𝗼𝗼𝗷𝗮: Ohh, so don’t you use Cloud monitoring for data pipelines? From my experience always start by tracking these four key metrics: latency, traffic, errors, and saturation. It helps you to check your pipeline health, if it's running smoothly or if there’s a bottleneck somewhere.. 𝗔𝗻𝗸𝗶𝘁𝗮: Makes sense. What tools do you use for this? 𝗣𝗼𝗼𝗷𝗮: Depends on the cloud platform. For AWS, I use CloudWatch—it lets you set up dashboards, track metrics, and create alarms for failures or slowdowns. On Google Cloud, Cloud Monitoring (formerly Stackdriver) is awesome for custom dashboards and log-based metrics. For more advanced needs, tools like Datadog and Splunk offer real-time analytics, anomaly detection, and distributed tracing across service. 𝗔𝗻𝗸𝗶𝘁𝗮: And what about data lineage tracking? How do you track when something goes wrong, it's always a nightmare trying to figure out which downstream systems are affected. 𝗣𝗼𝗼𝗷𝗮: That's where things get interesting. You could simply implement custom logging to track data lineage and create dependency maps. If the customer data pipeline fails, you’ll immediately know that the segmentation, recommendation, and reporting pipelines might be affected. 𝗔𝗻𝗸𝗶𝘁𝗮: And what about logging and troubleshooting? 𝗣𝗼𝗼𝗷𝗮: Comprehensive logging is key. I make sure every step in the pipeline logs events with timestamps and error details. Centralized logging tools like ELK stack or cloud-native solutions help with quick debugging. Plus, maintaining data lineage helps trace issues back to their source. 𝗔𝗻𝗸𝗶𝘁𝗮: Any best practices you swear by? 𝗣𝗼𝗼𝗷𝗮: Yes, here’s what’s my mantra to ensure my weekends are free from pipeline struggles - Set clear monitoring objectives—know what you want to track. Use real-time alerts for critical failures. Regularly review and update your monitoring setup as the pipeline evolves. Automate as much as possible to catch issues early. 𝗔𝗻𝗸𝗶𝘁𝗮: Thanks, 𝗣𝗼𝗼𝗷𝗮! I’ll set up dashboards and alerts right away. Finally, we'll be proactive instead of reactive when it comes to pipeline issues! 𝗣𝗼𝗼𝗷𝗮: Exactly. No more finding out about problems from angry business users. Monitoring will catch issues before they impact anyone downstream. In data engineering, a well-monitored pipeline isn’t just about catching errors—it’s about building trust in every insight you deliver. #data #engineering #reeltorealdata #cloud #bigdata

𝓢𝓾𝓹𝓹𝓵𝔂 𝓒𝓱𝓪𝓲𝓷 𝓓𝓲𝓼𝓻𝓾𝓹𝓽𝓲𝓸𝓷𝓼 𝓐𝓻𝓮𝓷’𝓽 𝓖𝓸𝓲𝓷𝓰 𝓐𝓷𝔂𝔀𝓱𝓮𝓻𝓮—𝓑𝓾𝓽 𝓓𝓪𝓽𝓪 𝓒𝓪𝓷 𝓗𝓮𝓵𝓹 𝓨𝓸𝓾 𝓟𝓻𝓮𝓭𝓲𝓬𝓽 𝓪𝓷𝓭 𝓟𝓻𝓮𝓹𝓪𝓻𝓮 From geopolitical tensions to energy shortages and shipping bottlenecks, supply chain shocks are now part of business-as-usual. We’ve seen how a delay at one port can ripple across continents—affecting inventories, pricing, and customer experience. Add climate-related events and policy shifts into the mix, and the volatility only grows. But amid the chaos, one thing offers 𝐜𝐥𝐚𝐫𝐢𝐭𝐲: 𝚍𝚊𝚝𝚊. ✅ 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 can flag disruptions before they escalate—by analyzing weather patterns, political instability, or supplier performance. ✅ 𝐑𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐦𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 helps organizations reroute logistics, rebalance inventories, and communicate proactively with partners and customers. ✅ 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐩𝐥𝐚𝐧𝐧𝐢𝐧𝐠 tools allow businesses to simulate “what-if” situations and prepare contingency strategies in advance. Supply chain resilience is no longer about just-in-time—it’s about being 𝗃𝗎𝗌𝗍-𝗂𝗇-𝖼𝖺𝗌𝖾. 🔍 The question is: 𝑨𝒓𝒆 𝒚𝒐𝒖 𝒖𝒔𝒊𝒏𝒈 𝒚𝒐𝒖𝒓 𝒅𝒂𝒕𝒂 𝒕𝒐 𝒑𝒍𝒂𝒚 𝒅𝒆𝒇𝒆𝒏𝒔𝒆… 𝒐𝒓 𝒕𝒐 𝒔𝒕𝒂𝒚 𝒐𝒏𝒆 𝒔𝒕𝒆𝒑 𝒂𝒉𝒆𝒂𝒅? #PredictiveAnalytics #DataDrivenDecisionMaking #SupplyChainManagement #RiskManagement #LogisticsStrategy

What if your home #WiFi could care for your loved ones? No wearables. No cameras. Just the existing WiFi signals in the house detecting if they fall or become inactive! In our latest work, we show how our #AI algorithm uses standard WiFi to track 2D #human #skeletons and detect #activities like #falls or inactivity, with accuracy close to camera-based systems, all while preserving privacy. This will be a large step forward in non-intrusive, intelligent elder care. - Paper: Younggeol Cho, Elisa Motta, Olivia Nocentini, Marta Lagomarsino, Andrea Merello, Marco Crepaldi, and Arash Ajoudani. "Wi-Fi based Human Fall and Activity Recognition using Transformer-based Encoder–Decoder and Graph Neural Networks" IEEE Sensors 2025. - Link to paper (open): https://lnkd.in/dpUB4gCS - Full video: https://lnkd.in/d9ji-P-h IEEE SENSORS Istituto Italiano di Tecnologia

𝐈𝐬 𝐭𝐡𝐞𝐫𝐞 𝐦𝐨𝐫𝐞 𝐭𝐡𝐚𝐧 𝐦𝐞𝐞𝐭𝐬 𝐭𝐡𝐞 𝐞𝐲𝐞 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐑𝐮𝐬𝐬𝐢𝐚𝐧 𝐝𝐚𝐫𝐤 𝐟𝐥𝐞𝐞𝐭𝐬' 𝐥𝐚𝐭𝐞𝐬𝐭 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐲? 𝐀𝐧𝐝 𝐰𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐢𝐭 𝐦𝐞𝐚𝐧 𝐟𝐨𝐫 𝐑𝐮𝐬𝐬𝐢𝐚𝐧 𝐜𝐫𝐮𝐝𝐞 𝐨𝐢𝐥 𝐟𝐥𝐨𝐰𝐬? In the past month, at least two vessels transporting Russian crude oil were targeted in the Red Sea. The UK, US, and the EU are cracking down on both traders and vessels trading above the price cap, with the entirety of Sovcomflot placed on the SDN list, effectively blacklisted. But are we seeing all the patterns? Based on Windward’s Sequence of Activities and new AI capability for ship-to-ship classification, our data points out several trends: ➡️ Between April 2023 and February 2024, there was a 54% increase in ship-to-ship transfers of crude or oil products in the Mediterranean, an increase that occurred immediately after the carrying vessel called a port in Russia. ➡️ There was another 108% increase in ship meetings in Southeast Asia, also conducted after port calls in Russia. ➡️ Between April 2023 and February 2024, there was a 556% (❗) increase in Commodity STS Meetings in the Mediterranean conducted after dark activity in Russia or the Black Sea, and a 127% increase in Commodity STS Meetings conducted after dark activity in Russia or the Black Sea. Who exactly are the vessels conducting this activity? Most are sailing under the flag of Liberia (19%), Marshall Islands (18%), Panama (15%), Singapore (5%), Greece (4%), Gabon (4%), Malta (3%), and Indonesia (3%). This means the majority of these vessels are sailing under Flags of Convenience, i.e., less regulated and potentially prone to risk. Moreover, Windward’s Compliance Risk classified 22% of these vessels as Medium Risk, 13% as High Risk, and 1% as Sanctioned. This is why as of February 19th, the UK requires a new attestation after every ship-to-ship transfer. In our Q4 Risk Report, released today, we analyzed that dark fleets grew by 29% to over 1,800 vessels (❗). The analysis above points to why. According to Bloomberg, there has been a global surge in seaborne Russian crude exports in the last month, yet Windward data indicates that this increase was not necessarily driven by Russian-flagged vessels. Simply put, Russian-flagged vessels have become too conspicuous as targets. So, the Russians are diversifying, taking it up a notch with their deceptive shipping practices. What does all of this mean for you? 1️⃣ Take a good look at the chain of events and holders' history of the cargos in which you trade 2️⃣ Take an even better look at cargoes that transferred mid-ocean in the Mediterranean and Black Sea. 3️⃣ Rank flags of convenience as a higher risk. 4️⃣ Employ AI to reduce false positives and avoid alerts from the various noises in the system. Windward's Q4 Report: https://lnkd.in/eeby7BMN Bloomberg's article: https://shorturl.at/hABCX #tankers #shipping #sanctions #duediligence

🚨 Plot twist: That location signal you thought came from GPS? Yeah… it’s actually your WiFi. 😏 Let’s settle this once and for all: Most people think tracking assets or goods always relies on GPS. But in many of our pooling applications, WiFi scanning is the real hero 🦸 — and here’s why: 📡 WiFi Scanning ≠ Connecting to WiFi We’re not logging in — we’re just scanning the environment. Devices detect nearby routers (SSID + signal strength) and triangulate location. It’s faster, uses less battery, and even works indoors (where GPS fails miserably — looking at you, warehouse corners 👀). ⚡ Lower Energy, Longer Life GPS modules are energy vampires. For pooled assets with long life cycles and limited power, WiFi-based location is a game changer. 🏭 Better Contextual Awareness WiFi signals can tell us where an asset is, but also what environment it’s in — warehouse vs. retail vs. on the move. 🧠 More Data = Smarter Systems With enough signal data, AI models can estimate location with surprising accuracy — often within a few meters. No satellite needed. No sky view required. 😂 So next time someone says, “Just use GPS for tracking”, kindly remind them: “Using GPS indoors is like using a sundial in a cave.”

After 30+ years in supply chain tech and visiting hundreds of warehouses globally, it's rare that something stops me in my tracks. UK startup Dexory just did exactly that. Here's what blew my mind: 🏗️ 39-foot-tall autonomous inventory scanners - literally the tallest robots on Earth 📊 10,000+ pallets scanned per hour with 99.9% accuracy 🧠 AI-powered warehouse optimization that learns and adapts 🌡️ Multi-sensor technology (HD cameras, temperature, humidity) perfect for cold chain 📱 Real-time digital twins creating living, breathing warehouse simulations But here's the REAL game-changer... Unlike most robotics companies that bolt solutions onto existing operations, Dexory thinks deeply about process integration. They're not just building robots - they're reimagining how warehouses think. Their AI doesn't just scan inventory. It predicts optimal storage locations, suggests put-away strategies, and creates digital twins that enable real-time simulations. The bigger picture? This isn't about full warehouse autonomy yet. It's about creating self-aware facilities - the foundation needed before everything becomes truly autonomous. My prediction: When you control the data, you control the flow. Don't be surprised if Dexory expands into real-time warehouse control systems. What's your take? Are we ready for 39-foot robots managing our supply chains? #supplychain #truckl #innovation

Amazon just rolled out a pretty cool update to Brand Metrics. Here's what you need to know: New features: -Category median benchmarks -Category top benchmarks -Percent change view Why it matters: 1. Compare your brand against category trends in real-time 2. Gauge if your growth is outpacing or lagging the category 3. Get instant insights without exporting data For example, say your beverage brand sees a 20% increase in shoppers. Sounds great, right? But what if the category median is up 25% and top performers are up 30%? This update helps you spot these crucial nuances instantly. The most useful tool is the percent change view. This feature will be huge for understanding your brand's performance in context. You can quickly see how you stack up during events like Prime Day, understand if a dip in numbers is brand-specific or category-wide, and measure the impact of your marketing efforts on awareness, consideration, and purchase metrics. My advice: Make the percent change view your first stop when analyzing performance changes. It'll help you differentiate between market trends and brand-specific issues, giving you the insights you need to make informed decisions.

𝗟𝗲𝘃𝗲𝗹 𝗨𝗽 𝗬𝗼𝘂𝗿 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆: 𝗪𝗵𝘆 𝗟𝗼𝗸𝗶 & 𝗧𝗲𝗺𝗽𝗼 𝗼𝗻 𝗖𝗹𝗼𝘂𝗱 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 𝗢𝘂𝘁𝘀𝗵𝗶𝗻𝗲 𝗘𝗟𝗞 & 𝗝𝗮𝗲𝗴𝗲𝗿 For teams hosting modern applications, choosing the right observability tools is paramount. While the ELK stack (Elasticsearch, Logstash, Kibana) and Jaeger are popular choices, I want to make a strong case for considering Loki and Tempo, especially when paired with Google Cloud Storage (GCS) or AWS S3. Here's why this combination can be a game-changer: 🚀 Scalability Without the Headache: 1 . Loki: Designed for logs from the ground up, Loki excels at handling massive log volumes with its efficient indexing approach. Unlike Elasticsearch, which indexes every word, Loki indexes only metadata, leading to significantly lower storage costs and faster query performance at scale. Scaling Loki horizontally is also remarkably straightforward. 2 . Tempo: Similarly, Tempo, a CNCF project like Loki, offers a highly scalable and cost-effective solution for tracing. It doesn't index spans, but rather relies on object storage to store them, making it incredibly efficient for handling large trace data volumes. 🤝 Effortless Integration: Both Loki and Tempo are designed to integrate seamlessly with Prometheus, the leading cloud-native monitoring system. This creates a unified observability platform, simplifying setup and operation. Imagine effortlessly pivoting from metrics to logs and traces within the same ecosystem! Integration with other tools like Grafana for visualization is also first-class, providing a smooth and intuitive user experience. 💰 Significant Cost Savings: The combination with GCS or S3 buckets truly shines. By leveraging the scalability and cost-effectiveness of object storage, you can drastically reduce your infrastructure costs compared to provisioning and managing dedicated disk for Elasticsearch and Jaeger. The operational overhead associated with managing and scaling storage for ELK and Jaeger can be substantial. Offloading this to managed cloud storage services frees up valuable engineering time and resources. 💡 Key Advantages Summarized: 1 . Superior Scalability: Handle massive log and trace volumes with ease. 2 . Simplified Integration: Seamlessly integrates with Prometheus and Grafana. 3 . Significant Cost Reduction: Leverage the affordability of cloud object storage. 4 . Reduced Operational Overhead: Eliminate the complexities of managing dedicated storage. Of course, every team's needs are unique. However, if scalability, ease of integration, and cost savings are high on your priority list, I strongly encourage you to explore Loki for logs and Tempo for traces, backed by the power and affordability of GCS or S3. Implementation screenshots shown below took me less than 2 nights to implement using argo-cd + helm + kustomize ... https://lnkd.in/gZyB5VZj #observability #logs #tracing #loki #tempo #grafana #prometheus #gcp #aws #cloudnative #devops #sre