Technology in Public Safety

Last month, a drone from Skyfire | AI was credited with saving a police officer’s life after a dramatic 2 a.m. traffic stop. Many statistics show that AI impacts billions of lives, but sometimes a story still hits me emotionally. Let me share what happened. Skyfire AI, an AI Fund portfolio company led by CEO Don Mathis, operates a public safety program in which drones function as first responders to 911 calls. Particularly when a police department is personnel-constrained, drones can save officers’ time while enhancing their situational awareness. For example, many burglar alarms are false alarms, maybe set off by moisture or an animal. Rather than sending a patrol officer to drive over to discover this, a drone can get there faster and determine if an officer is required at all. If the alarm is real, the drone can help officers understand the situation, the locations of any perpetrators, and how best to respond. In January, a Skyfire AI drone was returning to base after responding to a false alarm when the police dispatcher asked us to reroute it to help locate a patrol officer. The officer had radioed a few minutes earlier that he had pulled over a suspicious vehicle and had not been heard from since. The officer had stopped where two major highways intersect in a complex cloverleaf, and dispatch was unsure exactly where they were located. From the air, the drone rapidly located the officer and the driver of the vehicle he had pulled over, who it turned out had escaped from a local detention facility. Neither would have been visible from the road — they were fighting in a drainage ditch below the highway. Because of the complexity of the cloverleaf’s geometry, the watch officer (who coordinates police activities for the shift) later estimated it would have taken 5-7 minutes for an officer in a patrol car to find them. From the aerial footage, it appeared that the officer still had his radio, but was losing the fight and unable to reach it to call for help. Further, it looked like the assailant might gain control of his service weapon and use it against him. This was a dire and dangerous situation. Fortunately, because the drone had pinpointed the location of the officer and his assailant, dispatch was able to direct additional units to assist. The first arrived not in 5-7 minutes but in 45 seconds. Four more units arrived within minutes. The officers were able to take control of the situation and apprehend the driver, resulting in an arrest and, more important, a safe outcome for the officer. Subsequently, the watch officer said we’d probably saved the officer’s life. [Reach length limit; full text: https://lnkd.in/g3QdKp5Q ]

Security is no longer human-scale. It’s becoming autonomous. Would you agree? Right now, robots are already patrolling malls, monitoring borders, and securing critical infrastructure — quietly replacing traditional models of surveillance. But here’s what most people are missing: This isn’t a trend. It’s a multi-decade transformation of a $40B+ market. The global security robotics market alone is projected to grow from ~$16B today to over $44B by 2030, with ~15% annual growth. And that’s just one layer. Add drones, AI software, and surveillance infrastructure — and you’re looking at a much bigger ecosystem shift. What’s driving this? • Global security spending is rising fast (defense + infrastructure) • Labor shortages in physical security are accelerating automation • AI breakthroughs (Computer Vision, Machine Learning) are making systems predictive, not reactive Here’s where it gets really interesting: This market is evolving into a full-stack industry: → Robots (ground, aerial, underwater) → AI analytics platforms → Edge + cloud compute → Data pipelines processing massive real-time video streams And the biggest value? Not the robots. 👉 The intelligence layer. Let’s talk future. By 2030: • Drones will dominate aerial surveillance (fastest-growing segment) • Smart cities will deploy fully autonomous security grids • Security will shift from “incident response” → incident prediction • Robots will collaborate with humans, not replace them Beyond 2030? We’re heading toward: → Fully autonomous security ecosystems → Integration with smart infrastructure (traffic, energy, buildings) → AI agents making real-time security decisions → Robotics becoming a standard layer of every city But there’s a tension. Privacy vs Protection Automation vs Jobs Control vs Trust This will define the winners. Bottom line: We are not building better surveillance. We are building intelligent, always-on, predictive security systems at global scale. And the companies that master AI + data + robotics integration will define the next decade of infrastructure. #AI #Robotics #Security #SmartCities #FutureOfWork #Innovation

What’s common between an #airport and a #hospital? Both rely on advanced imaging technology to detect what the human eye can’t see—whether it's a concealed item in a carry-on or a hidden anomaly in a patient’s body. During a recent trip at one of the upgraded international airports, I noticed the new Analogic CT security screening machines. Unlike traditional X-ray scanners, these systems use Computed Tomography (CT) imaging, similar to what’s used in medical diagnostics. Instead of just providing a flat image (2D), CT scanners generate detailed 3D views, allowing security officers to analyze bags from multiple angles—without forcing passengers to remove laptops or liquids. 3D CT imaging offers transformational benefits: 1. Better accuracy, fewer false alarms – Just like in healthcare, a 3D view reduces uncertainty and enhances detection. 2. Faster and more efficient screening – No more unpacking half your carry-on at security! A good CT machine can scan 500-600 bags per hour. 3. Potential for AI integration – With machine learning, we may see even more intelligent threat detection. This got me thinking: despite being so convenient and efficient, why did it take so long for aviation security to adopt a technology that has transformed healthcare for decades? There are numerous challenges: 1. Cost and implementation – Upgrading thousands of security lanes globally is no small feat. 2. Training and adoption – Security personnel must adapt to a new way of analyzing images. 3. Balancing security with privacy – As with any advanced scanning, ethical considerations remain. As we see cross-industry tech adoption, it makes me wonder: What other innovations are waiting to bridge the gap between sectors? 1. Could AI-powered diagnostics in hospitals inspire predictive analytics for security? 2. Could autonomous screening systems reduce wait times like self-driving cars ease traffic congestion? The intersection of healthcare and security is more than just metaphorical—it’s a sign of how technology continuously finds new applications across industries. Have you seen any other examples where a breakthrough in one field reshaped another? Let’s discuss! Girish Nair Lalit Mistry Purushothaman KG

With more than 30 years in cybersecurity, I have seen this industry reinvent itself multiple times. Each shift was driven by a real change in how technology was adopted and how risk was created. We are now entering another such moment. The pace of AI adoption across businesses is unprecedented. Decisions, workflows, and infrastructure are increasingly autonomous, and they are moving faster than the security models most organizations rely on today. This is not a future problem. It is already happening. We had a decade to adapt to the cloud. With AI, we have months. At the same time, the security vendor landscape has evolved in a way that deserves honest scrutiny. Many solutions are platforms in disguise. In reality, a large number of them are portfolios of products that were built independently, acquired over time, and later brought together. This approach may reduce the number of vendors on a contract, but it does not reduce complexity. Boards understand this. They are not asking how many tools are deployed. They are asking whether the organization is spending the right amount for the level of risk it is prepared to accept, and whether that equation still makes sense as the pace of change accelerates. Answering that question requires more than incremental improvement. It requires a different model. A truly unified, agentic platform is not assembled from products. It is designed as a single system, able to reason, adapt, and respond across the entire environment. When security operates this way, something fundamental changes. The economics improve. Risk declines faster. And the gap between how fast the business moves and how fast security can respond begins to close. This is what we refer to as the new Agentic Platform Economy, an economic system where spend, risk, and resilience must stay in balance.

The future of emergency preparedness is connected, intelligent, and immediate. Technologies like 5G and the Internet of Things (IoT) are not just buzzwords; they are creating a powerful new nervous system for emergency response. In high-stakes situations, reliable communication and real-time data are paramount. 5G provides the ultra-fast, low-latency networks needed to transmit critical information instantaneously, while IoT sensors gather that vital data from the field. This partnership allows for: Real-time Situational Awareness: Sensors monitor everything from air quality in bushfires to floodwater levels, feeding live data to command centers. Enhanced Communication: First responders use 5G for high-definition video feeds and drone operations, ensuring commanders have eyes on the ground. Optimized Logistics: IoT devices track equipment and personnel, ensuring resources are deployed precisely where and when they are needed. This integration is closing crucial gaps. A study by Infosys projects that these technologies can reduce emergency response times by up to 20%, a difference that can save countless lives. From smart city initiatives in Australia leveraging IoT for flood monitoring to enhanced communication in remote areas of Pakistan via new connectivity, these technologies are transforming emergency management from a reactive effort into a proactive, data-driven science. Is your organization ready for the next generation of emergency response? #TechForGood #5G #IoT #EmergencyPreparedness #Gartner

With the current impact of cell network outages across almost all carriers in the US, it's a good time to talk about the future; actually, it's not even about the future, it's the present. Several years ago I started talking about having mobile robotics (air, ground and maritime robotics, like drones, rovers and submergible devices) be part of a mobile adhoc network or MANET. One example is a private mesh network, like Silvus Technologies provides. These communications solutions for high bandwidth video, C2, health and telemetry data are absolutely needed in today's environment and allow for a very flexible set-up and coverage; from a local incident scene, to a much larger area coverage, to entire cities or counties being covered. Why the need? While we in the drone industry originally focused on getting drones connected to a cell network, we quickly realized the single point of failure; the cell network infrastructure. Natural disasters, as well as manmade disasters, can impact these networks dramatically. An earthquake, hurricane, a solar storm, or a cyberattack, can take down these public networks for hours to days. And that includes public safety dedicated solutions like FirstNet or Frontline, during times when coms and data push is absolutely needed. Over the past couple of years we have seen the rise of mobile robotics deployments within private networks. While the defense side has done this approach for years, the public safety sector is still new to this concept. Some solutions integrate with a variety of antennas, amplifiers and ground stations, offer low latency, high data rates (up to 100+Mpbs), 256-bit AES encryptions and allow for a very flexible and scalable mobile ad-hoc mesh network solution. And most importantly - independence from a public network system. And now imagine you have multiple devices operating; a helicopter, a drone, a ground robotic, together with individuals on the ground, all connected and all tied into a geospatial information platform, like ATAK/TAK. Each connected device can become a node and extend the range. This is what I am calling building the Tech/Tac Bubble. This is not just the future, this is already happening with a handful of agencies across the US It's time to start thinking about alternative communication solutions and mobile robotics are an important part of leading the way. #UAV #UAS #UGV #Drones #network #MANET #Meshnetwork #publicsafety

Shenzhen is no longer experimenting with the future. It is deploying it. The city has officially launched airborne traffic police - a network of drones and drone hives managing accidents, violations, and congestion from the sky. 🚁 These systems do what human officers simply can’t: - Reach accident scenes almost instantly - Stream real-time aerial footage - Generate 3D reconstructions in minutes - Issue digital reports on the spot What used to take an hour now takes under five minutes. But this isn’t just reactive tech. It’s predictive. With AI-optimized patrol routes, the drones: - Detect violations nearly impossible to enforce from the ground - Identify congestion before it escalates - Coordinate with smart streetlights and police bikes for rapid response - Operate in heavy rain and strong winds This is what a real smart city looks like. Infrastructure that thinks, responds, and adapts in real time. Systems designed to keep millions moving safely and efficiently. Airborne enforcement isn’t science fiction anymore. It’s city management - Version 2.0. #SmartCities #UrbanInnovation #AI #Drones #FutureOfMobility #GovTech

We’ve obliterated 99% of Britain’s ancient rainforests. The Atlantic temperate rainforest - one of the rarest ecosystems on Earth - once covered vast stretches of the UK. Now, just 1% remains, thanks to centuries of deforestation for timber and agriculture. But what if we could change that with the help of technology? In Cornwall, The Woodland Trust has led a groundbreaking project using drones to sow 75,000 seeds of native trees across inaccessible landscapes - bringing life back to devastated land. If successful, this method could triple rainforest coverage in Devon and Cornwall by 2050. Here's why drones could be game changer for reforestation: 1️⃣ Reach inaccessible areas - steep slopes, remote locations, and fragile ecosystems where human tree-planting is impossible. 2️⃣ Faster and cheaper - a single drone can plant thousands of seeds in hours, covering more ground than a human team in days. 3️⃣ Higher efficiency - this trial aims for a 25% success rate, meaning one in four seeds takes root and grows into a tree, making this a scalable solution. Nature can heal, but only if we take bold, innovative steps to help it. What are your thoughts? Should we embrace more of this tech-driven restoration? Photo credit: Here Now Films

Recently, I came across a case from Maharashtra, where police solved a complex hit-and-run within 36 hours. The only clue was a vague description of a vehicle.     By deploying an AI system to analyze CCTV metadata from toll booths and traffic cameras, investigators used computer vision to filter thousands of vehicles, match visual attributes, and map the suspect path. What could have taken weeks or remained unsolved was closed in a day and a half.  This is a clear win for law enforcement efficiency. It’s a profound example of AI as a force multiplier for human good. The technology didn't replace investigators. It empowered them, turning an overwhelming data lake into a clear, actionable lead. It accelerated justice. We often speak about AI in terms of infrastructure. But stories like this ground that work.  Read More: https://lnkd.in/gD-hNXNw   #AIForIndia #AIForGood

🚨 AI + Font Forensics = ₹68 Lakh Tax Fraud Busted in Hyderabad 🚨 The Income Tax Department in Hyderabad recently used AI-powered font forensics to uncover a Long-Term Capital Gains (LTCG) fraud worth ₹68.7 lakh. A taxpayer claimed improvement costs from a bill dated 2002, but AI tools flagged the use of the Calibri font—which was only released in 2006–07. This inconsistency exposed the document as forged, prompting a revised ITR and additional taxes paid . 🔍 Why This Matters for Auditors & Risk Professionals 1. Innovative Forensics AI isn't just for big data and predictive insights—it’s now a frontline tool in document authenticity verification. Font analysis is a low-cost, high-impact method. 2. Red-flag Awareness It’s not enough to verify the content—verify the context. Details like font age, metadata timestamps, or even document origin can reveal fraud. 3. Regulatory Relevance Tax authorities are stepping up forensic capabilities. Expect similar methods to be applied in other regulatory areas—GST, money laundering, financial filings. 4.Upgrade Your Toolkit Incorporate similar forensic checks—font, metadata, version histories—into due diligence, vendor audits, expense claim reviews, and whistleblower investigations. ✅ Action Steps ✅ Add font & metadata analysis to your internal audit and investigation playbooks. ✅ Train teams to look beyond signatures—validate document authenticity at a granular level. ✅ Evaluate simple AI tools that can detect anomalies in fonts or document history. ✅ Share this knowledge in audit committees, risk forums, and compliance training. This case is another reminder: fraudsters adapt, but so must we. In a world where even fonts can betray deception, staying ahead requires curiosity, precision, and technology-backed scrutiny. What forensic techniques are you using to catch today’s more subtle frauds? #Forensics #Audit #RiskManagement #AI #InternalAudit #Compliance