Tag: AI

Finnish Skyfora raises €6.5M to turn GNSS telecom into real-time weather sensors

Skyfora, a Finnish weather data company building a new global data layer for weather and AI, has raised €6.5 million to transform GNSS telecom infrastructure into a real-time atmospheric sensing network.

The funding comes as demand for high-resolution weather data surges, driven by AI forecasting models, climate volatility, and the growing need for weather-resilient operations.

GNSS metrology system

Traditional weather forecasting relies on sparse networks of expensive ground stations, weather balloons, and radar systems — methods that leave vast gaps in coverage, particularly in urban areas and developing regions. Instead, Skyfora combines atmospheric physics, advanced signal processing, and artificial intelligence to extract weather intelligence from GNSS data.

GNSS meteorology turns every GNSS receiver into a weather sensor. The more receivers in an area, the higher the resolution of atmospheric data achievable.

GNSS signals traveling through the atmosphere are delayed by water vapor. By measuring these delays from multiple satellites and ground stations, Skyfora can create detailed 3D maps of atmospheric moisture — a critical input for weather forecasting.

Once the atmospheric data is captured and reconstructed, the system uses AI and high-performance computing to turn it into accurate, actionable forecasts.

Using existing GNSS receivers

Skyfora’s core technology uses GNSS receivers already installed in telecom networks, complemented by StreamGNSS hardware where telecom GNSS is not available, to measure atmospheric humidity with high precision and frequency. The GNSS signal delays are processed into real-time weather data streams that power next-generation AI weather models and forecasting systems, enabling more accurate, earlier, and hyperlocal predictions.

The company’s approach addresses a structural bottleneck in weather forecasting: most of the world’s atmosphere remains underobserved, and existing observation infrastructure cannot provide the data coverage and resolution required by modern AI models. Skyfora’s solution scales using existing infrastructure, requiring no new hardware at telecom sites.

Skyfora operates active deployments across multiple countries, working with telecom operators, meteorological institutions, forecasting partners and weather-affected industries to build out real-time atmospheric sensing on a global scale.

Latest capital round partners

The new capital will be used to accelerate the commercial scale-up of Skyfora’s software platform and atmospheric data products, expand partnerships with telecom operators, forecasting providers, meteorological institutions and weather-affected industries, and grow the team. The primary focus is on scaling deployment and market adoption: bringing Skyfora’s real-time data, API and atmospheric intelligence dashboard to market.

The round includes equity participation from Eviny Ventures, Ugly Duckling Ventures, Lumo Labs and the European Innovation Council (EIC) Fund, alongside non-dilutive funding from Business Finland.

The company is actively working to deploy datasets and customer opportunities across several countries in Europe, the United States, Africa and the Middle East.

June 9, 2026
Tern IDPS selected to accelerate autonomous satellite-free positioning

Tern has been named a winner of the U.S. Army’s xTechOverwatch for Unmanned Systems competition. TERN was selected from morethan 600 companies after hands-on Soldier testing at the Bush Combat Development Complex in Bryan, Texas, Oct. 27-29.

Tern developed an AI-powered Independently Derived Positioning System (IDPS) for position and navigation.

xTechOverwatch is the Army’s premiere event for accelerating autonomous systems, giving
soldiers the opportunity to use emerging technologies in real-world training environments and
provide critical feedback that drives iterative improvement.

The system has been tested across multiple tactical platforms in both on- and off-road environments, including active conflict zones.

Tern will now integrate IDPS directly with Army Transformation in Contact formations, where active-duty units will continue to validate the system in operational scenarios in 2026.

How IDPS works

IDPS has been proven to deliver uninterrupted, high-accuracy navigation in environments where GPS fails — tunnels, dense urban canyons, remote terrain, and GPS-denied zones. Tested by the U.S. Department of Transportation, it has sustained ±4-meter accuracy over extended distances without any satellite input, completing more than180 continuous miles GPS-free and performing flawlessly under live GPS spoofing in a conflict zone.

Tern’s IDPS gives the Army the ability to navigate their vehicles without the use of any
satellites, signals or infrastructure, using only map data and the sensors already on board.
Designed by former special operators who spent years navigating contested terrain without
satellite support, and developed with AI experts behind some of the fastest recognition systems
in the world, IDPS maintains precise, real-time location even when GNSS is jammed or
spoofed. The system has been tested across multiple tactical platforms in both on- and off-road environments, including active conflict zones.

Base maps. IDPS has a clear understanding of the roads ahead using preloaded map data — either publicly available or proprietary. This built-in knowledge means it can follow a logical path, even in places where satellites can’t reach, keeping navigation steady from the first turn to the final destination.

IDPS can stand alone or be configured to power a location manager and integrate with widely used navigation applications such as Google Maps, Waze, OSM, ESRI, ArcGIS and Apple Maps.

Sensor data. TERN’s IDPS leverages data from sensors already built into modern vehicles, such as wheel speed, steering angle, and 3D motion data , making these existing sensors smarter. Because this information comes directly from the vehicle, it works anywhere the vehicle can operate, making it a reliable foundation for location tracking in any environment, eliminating the need for additional expensive hardware, such as LEO satellites or terrestrial beacons. With a light computing and processing load, IDPS is can be a hardware or software based solution.

Artificial intelligence. IDPS uses a proprietary AI engine to fuse map data and sensor inputs into a real-time position. TERN’s advanced adaptive weighting algorithms measure and interpret the data from vehicle sensors and recalibrates those inputs in real-time, applied against the base maps to increase accuracy. Constantly self-healing, IDPS predicts, confirms, and refines the vehicle’s location, learning from each movement to maintain pinpoint accuracy without satellites.

November 21, 2025
UAV updates: DARPA advances UAVs, Area-51 RQ-170 investigation expands and more

Most people appear to be silently waiting for artificial intelligence (AI) to come up with a meaningful application beyond replicating jobs — one that actually helps people accomplish new tasks.

Daily news reports show one of the so-called “Magnificent Seven” technology companies pouring another billion dollars or more into AI data centers or basic development. Well now, the Defense Advanced Research Projects Agency (DARPA) has found a smaller AI company to develop a novel application for UAVs.

VISTA X-62A autonomous aircraft (Photo: Alex Lloyd/U.S. Air Force)

PhysicsAI has contributed AI “agents” to a highly modified F-16 for machine perception, intelligent behavior, control and adaptive learning to create an autonomous UAV, according to available information. The VISTA X-62A participated in a manned-unmanned dogfighting demonstration in September 2023, though the outcome has not been disclosed. Other platform enhancements include intelligent sensors through computer vision, EO/IR/RADAR sensor fusion and virtual reality simulations.

DARPA has engaged PhysicsAI to enhance UAVs so they can extend range and mission length by “soaring” — the technique birds use to find thermals in the atmosphere to climb to higher altitudes. AI agents will be designed, trained and tested to evaluate dynamic wind conditions, optimize flight profiles and perform soaring maneuvers.

DARPA intends to develop AI agents that will extend endurance by employing this bird-like soaring capability to reduce UAV onboard power usage and extend range and mission duration.

There is nothing new to report on the apparent drone crash Sept. 25, 2025, near the secretive base in Nevada, known as Area 51. The aircraft was attached to the 432nd Wing/432nd Air Expeditionary Wing at Creech Air Force Base in Nevada, about 57 miles southwest of the crash site. The 432nd operates MQ-9 Reaper drones, but the 33rd and 44th Reconnaissance Squadrons are also known to operate out of Creech and may operate RQ-170 Sentinel stealth drones.

RQ-170 Sentinel stealth drone thought to operate out of Cheech AFB Nevada (Photo: Lockheed Martin)

Famous (or infamous) for a 2023 reconnaissance operations in Iran, where one aircraft was apparently captured by the Iranians, the RQ-170 has been around since 2021.

The mystery surrounding the crash near Area-51 has grown somewhat since an inert training bomb and an aircraft panel were discovered at the crash site, but these items were not part of the damaged/destroyed crashed aircraft. In addition, the Air Force Office of Special Investigations (OSI) and the FBI have now been brought in to investigate. Enthusiasts who managed to get to the crash site recently found it cleaned completely, with no sign of spilt fuel or debris.

Troops in the field need information most — where the enemy is, their capabilities and what they’re doing.

One option: Launch a drone with video, infrared and radar, then use whichever works best depending on lighting, weather and whether the enemy jams signals. Better yet, call in a high-altitude surveillance drone like a GA-ASI Reaper that the enemy can’t see or hear. But that takes time, and one might not be available.

A new concept builds on an old precept — climb a tree and look at the opposition. But trees can be hard to find, difficult to climb and not high enough.

The answer to jamming and observational altitude: a tethered drone that a squad can carry. If the squad has a truck or Humvee, it can launch a tethered drone with no time limits because power comes up the tether with driving instructions while visual data goes back down. If necessary, move the ground vehicle closer and the drone moves with it.

Tethered drones serve any operation needing overview — rescue teams in disasters needing to see farther or a temporary communications hub, security operations searching for someone or something, monitoring or observing for infiltrators, initial surveys of difficult-to-access locations or military operations. Many other applications exist.

Most commercial and first-responder operations favor commercial or heavy-lift multirotor drones. Companies using multirotor drones include Hoverfly, Zenith, Fotokite, USaS, Advexure, Elistair, Kratos and Volarious.

Elistair Khronos Tethered DroneBox. (Photo: Elistair)

Kratos Aethon Tethered Drone. (Photo: Kratos)

If tethering drones to get really high, maybe use an aerostat that TCOM claims can operate from ground level to the stratosphere — pretty long tether needed! But applications also include anti-drone systems used to track and disrupt drone intruders.

Then a more recent entrant is Windlift who uses a fixed wing multi-prop drone on the end of a very long tether to gain altitude and to operate in the sort of wind conditions that might be found at times in many locations world-wide, on land or at sea — very windy to gale force winds, actually up to 55mph. Now this is pretty tough for any tether system, but Windlift has a variable cross section tether which mitigates wind-resistance. And their special application is to fly in a figure of eight pattern at high altitude — to generate electricity.

Windlift surveillance drone (Photo: Windlift)

Windlift power generator (Photo: Windlift)

This month brings a mixed bag of drone news, ranging from AI-driven “soaring” drones to an Area 51 drone crash mystery and an overview of tethered drones and their applications, including power generation. Who could have forecast these drone applications? Well, maybe the crashing part.

November 18, 2025
Pathfinder provides signal-resilient autonomy in navigation

Aero Drop Systems (ADS) has developed Pathfinder, a proprietary autonomous navigation framework designed to reduce dependence on GNSS-based positioning. Pathfinder is signal-resilient, capable of maintaining precision even in complete GNSS dead zones and unaffected by deceptive interference.

At the core of Pathfinder lies an array of sensors and advanced self-regulating logic driven by machine learning. Unlike traditional systems that treat GPS as a singular source of truth, Pathfinder fuses a constant stream of information from multiple internal and external domains and dynamically rebalances itself in real time as it evaluates, cross-verifies, and refines its positional understanding based on an algorithm that classifies the trustworthiness of each data stream.

The result is a self-correcting navigation intelligence that can anticipate changing conditions, isolate false data, and continue to perform when other systems cannot. This allows Pathfinder to sustain highly accurate navigation during satellite connection or radio frequency outages or when being targeted with jamming or spoofing.

Designed as a modular framework, Pathfinder can be integrated across a range of fully autonomous platforms operating on land, at sea, or in the air. Its flexible architecture makes it suitable for both commercial logistics and defense applications, where navigation integrity is critical to mission success.

Currently in the testing phase, Pathfinder is part of ADS’s broader initiative to develop resilient, autonomous logistics technologies capable of performing in contested and complex environments. ADS has confirmed that Pathfinder will serve as the core navigation technology for the platform Aerocrate. Aerocrate is a disposable, autonomous aerial delivery system that enables precise, reliable resupply without requiring recovery operations, staging areas, or active communication with the platform.

October 29, 2025
Frankfurt welcomes INTERGEO 2025 as geospatial tech tackles global challenges

Geoinformation has evolved from a specialist tool to an essential resource for government, business and civilian use. Whether captured from space or drones, analyzed through artificial intelligence (AI) or 3D visualizations, geographic data now, more than ever, drives critical decisions across industries.

INTERGEO 2025 exemplifies this transformation. From Oct. 7-9, the Frankfurt Exhibition Center will host the world’s leading conference and trade show for geodesy, geoinformation and land management, featuring more than 500 international exhibitors ranging from innovative startups to industry giants.

Three-Day Conference Program Features 100 Sessions
The INTERGEO Conference will present approximately 100 presentations and sessions over three days, drawing speakers from space agencies, United Nations organizations, government ministries and international technology companies.

Key topics include AI-powered remote sensing, urban digital twins, open data strategies, Earth observation for climate and crisis management and building information modeling (BIM) integration for infrastructure lifecycle management.

Keynote presentations such as “Earth Observation and Artificial Intelligence” and “Cartography for the Future” will provide forward-looking insights, while panel discussions on digital sovereignty and standardization will address strategic frameworks. Each session demonstrates how geoinformation serves as the critical foundation for climate adaptation, disaster preparedness, urban development and infrastructure protection.

Opening Day Features Space Technology Focus

DVW President Prof. Rudolf Staiger will open INTERGEO on Tuesday, Oct. 7, followed by a keynote from Johann Dietrich Wörner, space coordinator for the state of Hesse. His presentation, “Earth Observation and Artificial Intelligence,” will explore how AI transforms massive Earth observation datasets into actionable insights for climate, agriculture and urban planning projects.

Prof. Serena Coetzee of UNU-FLORES will deliver the German Cartography Congress keynote on Wednesday, Oct. 8, addressing cartography’s evolution amid growing geodata volumes and governance challenges.

Thursday morning’s panel discussion, “Digital Transformation – Perspectives, Trends and Theses,” will examine the need for reorienting geoinformation management to foster innovation and collaboration.

Revolutionizing Geospatial Data Analysis

AI is accelerating the transformation of raw data into actionable insights, fundamentally changing how professionals work with geoinformation. The session “AI-Based Analysis of Remote Sensing Data for Updating the ATKIS Basic DLM” demonstrates practical applications in public administration.

The Hessian Administration for Soil Management and Geoinformation uses AI methods to automatically detect landscape changes, significantly improving the quality and timeliness of digital landscape models.

Urban digital twins are rapidly advancing from static models to powerful operational platforms. The session “From Data to Insights: Visualization Technologies for Next-Generation Digital Twins” will showcase how modern visualization makes complex systems accessible and accelerates planning processes.

The research project “DigitalCities4Us” illustrates practical applications, using high-resolution 3D data to enable barrier-free urban planning and improve accessibility for people with mobility restrictions.

Additional sessions will examine implementation across administrative levels. “The Digital Twin NRW: A Practical Report” presents a statewide geospatial data infrastructure that is freely accessible and continuously developed. The city of Zurich will demonstrate its transition from traditional geospatial data infrastructures to multifunctional twin platforms.

Geodata infrastructures, open data and data spaces form the backbone of digital transformation and serve as key prerequisites for digital sovereignty. Multiple sessions will emphasize the importance of stable, future-ready geodata infrastructure.

Standardization receives particular attention through presentations like “Three Perspectives, One Goal: Digital Sovereignty through Open Standards in BIM and GIS” and the position paper “Official Geodata as a Basis for Digital Processes in Planning, Construction and Operation.” These sessions demonstrate how uniform standards for data exchange between geographic information systems and building information modeling can accelerate planning, construction and operational processes.

The position paper represents a joint initiative of buildingSMART Germany, the Working Committee of the Surveying Authorities and the Federal Association of Publicly Appointed Surveyors.

Critical infrastructures require precise, reliable data to minimize risks. The presentation “Regional and Effective Flood Protection in the State Capital of Düsseldorf” demonstrates how geoportals and flood forecasting tools prevent flooding and strengthen urban infrastructure resilience.

Bringing Innovation to the Exhibition Floor

Registration is now open at the INTERGEO website. The INTERGEO 2025 team looks forward to welcoming attendees to the Frankfurt Exhibition Center from Oct. 7-9.

September 25, 2025
Safran launches AI tool for GNSS simulation automation

Safran Electronics & Defense has unveiled Skydel AI, a breakthrough in GNSS simulation technology that uses artificial intelligence (AI) to automate and simplify simulation scenario setups.

Skydel AI streamlines GNSS simulation scenario creation through intelligent automation and an intuitive interface. Using natural language commands, Skydel AI allows users to query GNSS/Skydel topics, request assistance and dynamically configure simulation parameters by creating Python code for use by Skydel. The technology eliminates complexity and significantly reduces setup time.

“Soon available as part of Safran’s Support offerings, Skydel AI can help customers drastically improve their development cycles by accelerating manual scenario tuning and reducing long test cycles within Skydel,” said Pierre-Marie Leveel, program director for PNT at Safran. “Already established as the most flexible, robust, and accurate GNSS simulation engine, Skydel never stops innovating and delivering what the market requires – whether it is more realism, higher accuracy, more environment complexity, or ease of use.”

The company also introduced an AI-powered tropospheric model that enhances Skydel’s tropospheric simulation using real-time weather data and AI predictions to improve wet delay accuracy. Integrated with the Open-Meteo API and Skydel’s system, it relies on a neural network trained on 14 million samples from 221 GNSS stations, delivering up to 88% more accuracy. This model will be available in a future Skydel release.

The technical breakthrough reflects Safran Electronics & Defense’s commitment to redefining GNSS simulation with intelligent, adaptable and high-performance solutions for mission-critical applications.

September 12, 2025
The spatial AI revolution: Entering the age of intelligence

The intriguing paradox about the information age is that it relies on semiconductor chips, which are fundamentally made from sand (silicon dioxide) — the most tangible and seemingly infinite resource on Earth. Yet, in 2023, the global digital storage capacity reached 110 zettabytes (110 followed by 21 zeros), which is a staggering figure; in fact, it is 15,000 times more than the number of grains of sand on Earth and it’s doubling every three years. The information age is suﬀering from excess information. Data is consuming the universe.

The velocity and quantity of information are overloading the ability to process it. This causes data-driven decision-making systems to fail. The limiting factor is human cognitive capacity to select, prepare and process the data, plus the ability to analyze it for meaningful insights. It is reminiscent of the early days of the Corona satellites of the TALENT KEYHOLE (KH) mission series that began in the 1950s during the height of the Cold War.

Understanding activities behind the Iron Curtain was critical for national security. The KH
satellites were expensive to launch and had short life spans. They used rolls of wet film dropped from space and captured by specialized aircraft with hooks to catch the canisters in mid-air. The low-resolution images (3 m to 5 m per pixel) were processed manually in darkrooms. Teams of 100 specialists, using razor knives and scotch tape, meticulously pieced together image strips into massive mosaics spanning several square meters. Working around the clock, assembling the full image would take up to five days, with subsequent analysis requiring another week. In total, from catching the film canister to delivering a final intelligence report, it took 17 days — a testament to imagery intelligence in the industrial era, characterized by massive operations demanding significant time and manpower, but it was too expensive and unsustainable.

Photo: PRESIDENT EISENHOWER awards Capt. Mitchell, USAF, C-119 pilot, the Distinguished Flying Cross for the first ever capture of a film cartridge dropped from space, in a photo circa 1960. cia.gov/resources/csi/static/corona.pdf

“We live in a world where there is more and more
information, and less and less meaning.”

— Jean Baudrillard,

“Simulacra and Simulation,” 1994

In 1976, the technological landscape shifted dramatically with the launch of the KH-11 satellite, which could transmit 15 cm resolution images digitally to ground stations and was capable of distinguishing objects as small as a dinner plate. The satellite dramatically compressed intelligence-gathering timelines. Processing and analysis time decreased from 17 days to mere hours. The first digital image was shown to President Carter. That first image is believed to be of ongoing tensions in the Middle East, but it symbolized more than the triumph of technology; it represented a fundamental shift marking the end of the industrial era and ushered in the information age.

Advancements in imagery were paralleled by developments in mapping, driven by the need for accurate spatial referencing. Various technologies throughout the 1970s oﬀered partial solutions, but a solution did not happen until 1981 when Esri introduced Arc/INFO, a breakthrough geographic information systems (GIS) software that could operate on minicomputers instead of huge mainframes. That formed the basis of modern spatial analysis and visualization technologies; coming together with digital imagery is what allowed the information age to overtake the industrial era.

In 2025, a similar technological transformation currently is underway. As the amount of information overwhelms existing systems, artificial intelligence (AI) is emerging as the solution. The information age is transforming into the intelligence age, where big processing meets big data. Advanced algorithms, machine learning and large language models (LLM) can swiftly and eﬃciently handle vast amounts of information. So, with data being the new oil, AI is the refinery.

The Esri Federal GIS Conference in February could have been promoted as the “Dawn of GeoAI” conference. The term Geo AI is a subset of Spatial AI, and it is in its infancy. Esri is incorporating AI into many of its applications. Companies at the expo were teasing Spatial AI solutions in their products and services.

What is Spatial AI?

When the transformative power of AI is combined with spatial information systems, magic happens. Value is created that did not exist before.

Spatial intelligence is the ability to think, visualize and understand in three dimensions. It is one of the primary types of intelligence. Currently, Spatial AI is capable of interacting with analysts using natural language to build models and perform tasks. Similar to so much else happening with AI, its capabilities are increasing rapidly.

Photo: A CORONA SATELLITE image of Moscow captured May 28, 1970, as part of the TALE…

With iterative learning, the AI repeats a task millions of times on various training data to perfect its abilities, running through diﬀerent scenarios multiple times with diﬀerent datasets while completing multiple tasks. The AI quickly learns and can eventually surpass humans. This makes AI a super tool.

Combine that capability with AI’s ability to access and infer an entire compendium of knowledge on a subject. The AI is able to ingest text, images, audio and video in minutes, and then reason and understand them all within the context of the parameters provided. Through its own AI agents, it will automatically run functions to garner insights, and then communicate those results through data visualizations, text, audio and natural speech. Spatial AI is an evolved form of AI able to understand data in the context of space and time within the body of knowledge it can access. It will monitor everything in real time to identify anomalies and hidden patterns and provide deep insights. It doesn’t just solve the information overload dilemma for data-driven decision-making, but it enhances it far beyond expectations.

The Coming World of AI Assistants

The future is already here. Reality is approaching science fiction at warp speed. A person living 100 years ago would only be able to understand the world of today as magic; and likewise, the world 20 years from now will appear magic to us.

Interfacing with a Spatial AI system is similar to the multi-dimensional world we already exist within. Flat screens, keyboard and mouse will be secondary tools behind natural language and natural gestures and immersive experiential environments. The Spatial AI- enabled world will blur the lines between what is virtual and what is real. Jobs, businesses and the economy already are transitioning. The most well capitalized businesses are investing in this new technology.

One of the industries at the forefront is healthcare. Imagine you are a neurosurgeon. Your patient has a glioblastoma identified by the MRI/CT scans uploaded into the Spatial AI Medical Assistant called SAIMA (pronounced Sāmă; when speaking with the system, you call it “Sammi”). The MRI/CT scans show a 3D model of the patient’s brain, highlighting the glioblastoma in red. Placing the integrated augmented reality (AR) glasses on, you can zoom in on the glioblastoma to see the extent of the growth and view it from any angle. This helps formulate a surgery plan. The patient’s medical records are in SAIMA along with the corpus of knowledge about glioblastomas. SAIMA is regularly updated with the latest algorithms and models. After reviewing the preliminary data, you have SAIMA run the spatial analytics and all the applied functions on the data. It takes approximately 35 minutes to complete. During that time, you review the SAIMA updates and go to lunch. You receive a text message from SAIMA after it completes its processing, letting you know it is finished without encountering any issues. SAIMA works with a system called VisAR, which is a precision surgical navigation system. After returning to your oﬃce, you put on the VisAR glasses to begin the review. Sammi begins by showing you the glioblastoma and pointing out it is a large, heterogeneous mass located in the frontal lobe and appears to be 4 cm to 5 cm in diameter, in an irregular shape with nodular and cystic components. As it goes through the review, it zooms in and rotates the 3D image, highlighting the exact area being talked about. You interrupt Sammi during this review and ask if the patient has been experiencing motor function issues since the tumor is in the frontal lobe, and you continue to probe further in a natural conversational tone as you delve deeper into the analysis. The conversation between you and Sammi is recorded and added to the file.

The review with Sammi takes several hours, during which a high-confidence surgery plan is developed that you will present to the multidisciplinary tumor board, who will further query SAIMA. This thorough process ensures the best results and further trains SAIMA about glioblastomas, which will be used for a post-surgery debrief and for insurance purposes. Following a successful board meeting, SAIMA proceeds to reserve the operating room, schedule the patient, and create a detailed surgery plan with specific duties and exact times for each member of the surgical team. This plan is then disseminated to all members of the surgical team and preoperative staﬀ. A detailed surgical procedure file is generated, which serves as a navigation file, similar to Waze or Google Maps, providing step-by-step instructions to guide the surgery. This file will be loaded into ROSA (Robotized Surgical Assistant), a high-precision robotic surgeon.

On the day of the surgery, you wear special Bluetooth gloves that are synced with the SAIMA/VisAR glasses and ROSA. In real-time, magnified between 15x and 40x, you observe ROSA surgically removing the cancerous tissue. Overseeing the process, you see a tumor that has spread beyond the original CT/MRI scan and zoom-in on the tumor, and you take control of ROSA to manually remove the tissue. The surgical system uses a “diﬀerential engine” concept to scale down the surgeon’s movements to match the magnification level of the procedure, allowing for precise and delicate tissue removal. This means that the surgeon’s natural movements are reduced to a smaller, more precise scale, enabling accurate and intricate procedures. For example, a 1 cm movement by the surgeon might be translated into a 0.1 mm movement of the robotic arm, allowing for high-precision work. The system is dependent upon a high-level of spatial intelligence to make those calculations in real-time.

Afterward, you return the surgery back to the automated control of ROSA to follow the surgical procedure file plan. Throughout the fully immersive procedure, you speak with Sammi in a calm, natural language and responsive manner.

The patient, a married middle-aged father of two, not only survives but thrives because of the accurate analysis of SAIMA and the precision of ROSA, with you overseeing the entire process. The Spatial AI-based surgical system allows you to do what you wanted to do as a neurosurgeon and save people’s lives.

Nothing is Permanent Except Change

Breakthrough innovations, such as the internet, have changed the world. Spatial AI is going to do the same. These technologically driven schisms are huge opportunities. One can only speculate how it will alter the future. Once a technology takes hold, and it becomes obvious there is no going back, its adoption will accelerate, and in those moments, careers make exponential leaps. Those in front of it will make substantial gains. Position yourself accordingly. Learn about Spatial AI and Geo AI. Carve out your own specialty, such as Spatial AI/AR (augmented reality), Spatial AI/VR (virtual reality), Spatial AI/XR (mixed reality), and Spatial AI/FMV (full motion video). The future is yours to imagine.

Photo: William Tewelow

WILLIAM TEWELOW is a designated Geographic Information Systems Professional. He has a master’s degree in Organizational Leadership with a focus on Performance Management, a bachelor’s degree in Intelligence Studies focused on geospatial intelligence, and an undergraduate degree in Geographic Information Technologies. William retired from the Federal Aviation Administration in 2025 after 16 years in various roles supporting geospatial information for aviation operations in the national airspace. He is a graduate of the management fellowship Program for Emerging Leaders where he served on special assignment to the Department of Transportation, leading a national strategic geospatial initiative under the authority of the White House Open Data Partnership.

September 8, 2025
AI maps: The digital infrastructure driving autonomous systems

Each day, millions of transportation decisions are made without a driver manually choosing a route or reacting to road signs. Trucks are rerouted around traffic hours before a jam appears. A vehicle slows down in a school zone, even without seeing a sign. A delivery service dynamically dispatches drivers based on weather and wait times.

These are not just conveniences; they are outcomes of location intelligence working behind the scenes, powered by artificial intelligence (AI) and real-time mapping.

At the heart of these systems lies a fundamental shift: maps are no longer static guides for humans. AI is unlocking a new era of computing and autonomous systems that will drive industry innovation and reinvention for years to come. Maps have become live, machine-readable software that enables automation at scale. Accenture’s Technology Vision 2025 report found large-language models (LLMs) are giving machines and robots more autonomy in the physical world, allowing them to better understand the physics of their environments, have spatial awareness, interact with people and understand complex instructions. This evolving autonomy is critical for autonomous vehicles, smart logistics and other systems that rely on real-time, AI-powered mapping to sense, decide and act.

Whether it’s advanced driver assistance systems (ADAS), predictive logistics, EV range optimization or smart city operations, AI-powered mapping is fast becoming the connective tissue between sensing, decision-making, and action. It all begins with location data that is collected, interpreted and delivered in real time.

From Navigation to Infrastructure: The Evolution of the Map

Throughout the past two decades, digital maps have evolved from a novelty to a necessity. The early wave of turn-by-turn GPS tools was designed for humans — to get us from one point to another using the shortest or fastest route.

Today, we are witnessing a new paradigm. As autonomy becomes embedded in vehicles, delivery operations, and mobile robotics, we need a new kind of map — one built for machines.

These maps must be able to see, react and even predict. They must be continuously updated with real-time inputs, capable of interpreting events and structured in a way that allows for automation logic. In other words, they must be intelligent; and that intelligence comes from AI.

AI-Powered Maps: What Makes Them Different?

A live, AI-powered map is far more than a digital representation of roads and intersections. It begins with a foundational base layer — detailed information about road geometry, lanes, speed limits, signage and more. However, what sets these maps apart is how they evolve in real-time to reflect the dynamic nature of the world around us.

They incorporate constantly changing inputs like traffic flow, construction activity, road closures and weather conditions — data streams that traditional static maps cannot accommodate. Beyond reacting to real-time events, AI maps also understand context. They may recognize nuances such as school zones that change by time of day, hazardous intersections, low-clearance bridges, and the availability or compatibility of EV chargers at nearby locations.

Crucially, AI-powered maps don’t just describe what’s happening – they anticipate what might happen next. Fueled by billions of data points collected from vehicles, sensors, satellite imagery and crowdsourced sources, these systems use predictive modeling to foresee traffic build-ups, potential hazards or shifts in road accessibility.

The result is a map that doesn’t merely guide but thinks — a constantly updating model of the world designed not for human eyes alone, but for machines that need to make decisions in real-time.

AI fuses these elements, constantly recalculating and enriching the map to reflect what’s happening now and what might happen next.

For this to work, mapping platforms must ingest the billions of data inputs. AI models then validate, filter and extract insight from this data — turning raw input into actionable intelligence and guidance.

Why AI Maps Matter in the Vehicle

Modern vehicles are increasingly defined by software, and that software needs a constant, reliable connection to the outside world.

ADAS features, such as intelligent speed assistance (ISA), lane keeping and predictive cruise control, depend not only on sensors like cameras or radar, but also on high-quality map data to anticipate what’s ahead.

For example, speed limit detection based solely on onboard vision can fail in poor weather or when signs are obscured. But when paired with verified, map-based data, continuously updated by AI, vehicles can make safer, more consistent decisions. As regulators in the EU and beyond mandate ISA systems in new vehicles, AI-enhanced maps are becoming a tool for regulatory compliance, not just convenience.

As OEMs continue their shift toward software-defined vehicles (SDVs), they increasingly treat maps as a core software module, critical to the operation of the vehicle itself, not just a navigation layer.

In the era of SDVs, maps are evolving into a foundational software service used not just to get somewhere, but to determine how and when it is safe to drive.

How AI Maps Support the EV Transition

One of the most significant barriers to widespread EV adoption is range anxiety: the fear that a driver won’t reach a charger in time, or that the charger will be in use or out of order. AI-powered maps help directly address this.

By combining real-time charger availability, plug compatibility, dynamic traffic conditions, topography, and vehicle battery status, intelligent routing systems can not only suggest optimal charging points, but also reroute on the fly as conditions change.

This level of intelligence is essential for EV fleet operators, especially those in logistics, ride-hailing or municipal transit.

AI-powered maps also leverage charger usage patterns, traffic flows and gaps in the network to help cities plan where to place new charging infrastructure.

In this way, location intelligence doesn’t just support EVs on the road but helps accelerate adoption.

Why AI Maps Matter in the Supply Chain

A HERE Technologies ‘On the Move’ survey found only 25% of transportation and logistics professionals are leveraging AI in supply chain management. Yet, the use cases for AI-powered mapping are plentiful.

Fleet operators face daily challenges: delays, emissions targets, labor shortages and delivery windows that shift by the hour. They’re actively seeking technology-based solutions. McKinsey projects the autonomous heavy-duty trucking market could reach an aggregated $616 billion in 2035 in China, the United States and Europe.

AI-powered maps help address many of these challenges. By combining real-time traffic information, road restrictions (e.g., weight limits, low bridges), and predictive analytics, intelligent maps help logistics operators optimize every mile.

For example, dynamic routing can avoid areas of congestion hours before they peak, based on machine learning models trained on historical and live data. AI can prioritize delivery orders based on customer availability, time-of-day restrictions or weather disruptions.

Beyond routing, maps also assist in asset tracking and risk management. Telematics systems that combine GNSS positioning with AI-based location intelligence can detect anomalies in driving behavior, flag out-of-route events and improve operational safety.

The results are evident and tangible: lower fuel consumption, reduced delivery times and higher fleet utilization.

GNSS and Geospatial Foundations

It’s important to underscore that these intelligent maps still depend on foundational technologies like GNSS. Without reliable satellite-based positioning, none of these applications (ADAS, EV routing or predictive logistics) would be possible.

But GNSS alone isn’t enough. Real-time location must be contextualized. An accurate lat/long fix is powerful, but the system needs to know: What road is that on? What’s the speed limit? Are there known hazards? What time of day is it? Is it raining?

This is where geospatial data, fused with AI and layered into live maps, becomes transformational. The future isn’t about replacing GNSS — it’s about expanding what’s possible when GNSS is augmented with AI, context and prediction.

Looking Ahead: Mapping as Mission-Critical Infrastructure

As autonomy increases across industries — from fully autonomous vehicles to self-driving delivery trucks to smart city systems — AI-powered maps will underpin critical operations.

AI-powered maps will be essential to the flow of goods, the safety of passengers and the predictability of city infrastructure. These systems must be continuously updated, machine-readable, context-aware, predictive and scalable. They also must be built with privacy, security and compatibility in mind. Governments, automotive manufacturers, technology providers and mapping platforms will need to collaborate — not just on data collection, but on standards, governance and interoperability.

Quiet Engine of Autonomy

We often focus on the visible outputs of automation: the driverless shuttle, the drone delivery, the smart traffic signal. However, none of these can function without a live map underneath, enabling every decision, in every moment.

Digital maps have become the quiet engine of autonomy. With the power of AI, they’re becoming smarter, faster and more essential every day.

For professionals in GNSS, geospatial intelligence, and positioning systems, this shift opens new territory where location isn’t just about where things are, but also about what’s happening, why it matters and what should happen next.

In this world, AI-powered maps are no longer a tool. They’re infrastructure.

July 21, 2025
IBM advances geospatial AI to address climate change

Image: IBM/NASA

IBM, a global technology provider, has released its latest geospatial artificial intelligence (AI) initiative to address climate change. These efforts involve collaborations across various regions and uses advanced AI models designed for geospatial applications.

Central to these initiatives is IBM’s geospatial foundation model, developed jointly with NASA. These models aim to generate environmental insights and solutions related to climate change. Unlike traditional AI models, these use a vast amount of climate-relevant data to accelerate the analysis of various environmental aspects that are affected by climate change.

“AI foundation models utilizing geospatial data can be a game-changer, allowing us to better understand and address climate-related events with unprecedented speed and efficiency,” said Alessandro Curioni, IBM fellow and vice president of Accelerated Discovery.

Analyzing urban heat islands in UAE

IBM and the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) have partnered to map urban heat islands in Abu Dhabi using a fine-tuned version of IBM’s geospatial foundation model. The goal of the project is to understand the impact of local landscapes on temperature anomalies, the company said. The initial results show a decrease in heat island effects, which can provide valuable insights for future urban design strategies.

Reforestation and water sustainability in Kenya

In partnership with Kenya’s Special Envoy for Climate Change, Ali Mohamed, IBM is supporting the National Tree Growing and Restoration Campaign. The initiative aims to plant 15 billion trees by 2032, particularly in critical water tower areas affected by deforestation. IBM’s geospatial model powers a digital platform to track tree planting activities, aiding local efforts in restoring forests and measuring carbon sequestration impact.

Elevating climate resiliency in the UK

In collaboration with the Science and Technology Facilities Council (STFC) and Royal Haskoning DHV, IBM is developing AI-driven tools for climate risk assessment in the UK. These tools will focus on assessing weather impacts on aviation operations, the company said. Additionally, the TreesAI research project aims to map areas suitable for tree planting to mitigate surface water flooding and offer urban developers a digital planning platform.

IBM extends collaboration with NASA for weather forecasting

IBM and NASA have partnered to develop an AI foundation model dedicated to weather and climate applications. The collaboration aims to enhance the accuracy and speed of weather forecasting, predict wildfire conditions and understand meteorological phenomena. IBM researchers will work closely with NASA to train and validate this model, IBM said.

December 7, 2023
MWC returns to Las Vegas
Image: GSMA

The Mobile World Conference (MWC) returns to the Las Vegas Convention Center on September 26 to 28, 2023.

The event will feature exhibition from major U.S. operators, including AT&T business, T-Mobile business, and Verizon business as well as new sessions dedicated to sports and entertainment, software developers and the GSMA’s SEC CON event.

MWC, in partnership with the Cellular Telephone Industries Association (CTIA), invites industry leaders and attendees to connect and discuss topics such as the industry’s transition to a circular economy, the future role of artificial intelligence (AI) in society, and what comes after 5G.

To reflect the United States’ position as a global technology hub and a market at the forefront of 5G innovation, the event is centered around four key themes:
- 5G Acceleration, as adoption explodes to become the most common mobile technology in North America by 2025.
- Age of AI, as the world awakes to the opportunities and challenges of generative AI.
- Digital Everything, as the expansion of digital technologies is felt across every industry, from sports and entertainment to manufacturing, financial services and smart mobility.
- Enterprise Mobility, as the revolutionary phase of 5G in enterprise is well underway.
The event will feature a variety of keynote speakers, including Amanda Toman, the director for the Public Wireless Supply Chain Innovation Fund at the National Telecommunications and Information Administration (NTIA) within the U.S. Department of Commerce.

For the first time, the GSMA will bring its SEC CON event to MWC Las Vegas on day two, welcoming leading security experts to explore the importance of keeping telecoms infrastructure secure in times of conflict.

A full directory and registration can be found on the MWC Las Vegas website.
September 7, 2023
Qualcomm, Hyundai partner for PBV infotainment

Image: Hyundai Motor Group

Qualcomm has entered a technology agreement with Hyundai Motor Group to integrate its Snapdragon Automotive Cockpit Platform into Hyundai Motor Group’s purpose-built vehicles (PBV).

The infotainment systems on the PBVs will use Snapdragon Automotive Cockpit Platforms for a “holistic, seamlessly connected and smart user experience,” Qualcomm said.

The PBVs are designed to deliver transportation, comfort, logistics, commercial and healthcare services. The latest generation of Qualcomm’s Snapdragon platform benefits from optimized power consumption, high-definition graphics and immersive multimedia and audio.

According to Qualcomm, the latest generation of Snapdragon Automotive Cockpit Platforms offer optimal power consumption while providing top-tier graphics as well as top immersive multimedia and audio experiences.

The platforms offer location services, emergency calling, noise reduction, and dual SIM capability as well as cloud-based monitoring and management systems. Using Qualcomm’s artificial intelligence (AI) engine and machine learning (ML) capabilities for intuitive and intelligent systems, Snapdragon can support digitally advanced applications, including in-vehicle virtual assistance and adaptive human interfaces. It can also facilitate natural communication between the vehicle and passengers for added safety and comfort.

The platform also employs dynamic configuration management to ensure vehicles are kept up to date. Reliable cloud-based vehicle monitoring and management also is possible through cloud service solutions.

Qualcomm and Hyundai Motor Group have been collaborating since 2011 on in-vehicle mobile communications using Snapdragon Automotive Connectivity Platforms.

September 5, 2023
Cloud Ground Control by Advanced Navigation releases product for UAVs and robotic vehicles

Credit: Cloud Ground Control by Advanced Navigation

Cloud Ground Control, an Advanced Navigation company, has released its cellular micro-modem, the CGConnect. Using 4G/5G networks, CGConnect links UAVs or robotic vehicles to Cloud Ground Control’s cloud-based UAV fleet management platform — enabling live-streaming, command and control from a web browser.

CGConnect can securely connect UAVs and vehicles into one autonomous fleet across land, sea and air, regardless of manufacturer or model. This provides mission planners and operators with full situational awareness for search and rescue, emergency response and disaster relief.

Artificial intelligence (AI) algorithms run in the cloud, relaying real-time camera feed data to the end user to support missions such as object detection, tracking and thermal imaging. The flexible and customizable open platform operates on industry standards, which multiplies potential product applications and enables autonomous vehicles and payloads to operate as a coordinated fleet.

CGConnect’s high-grade security safeguards data and IP from vulnerabilities and security breaches, helping users meet compliance obligations. Additionally, CGConnect supports edge AI to perform intensive object identification and classification directly on the vehicle for dynamic missions.

CGConnect is available for pre-order. An OEM option is also available.

May 2, 2023