Beyond GPS: The Future of Location Data

For over two decades, the Global Positioning System (GPS) has been the backbone of location data and location-based services—from helping us find the nearest coffee shop to powering precision agriculture. location data. But as the world becomes more connected, mobile, and data-driven, GPS is showing its age. From urban canyons that block satellite signals to indoor environments where GPS falters completely, the limitations are becoming more pronounced. The future of location data is no longer tethered to satellites alone.

We’re entering a new era—one where GPS is just one piece of a complex puzzle. Emerging technologies like Wi-Fi RTT (Round Trip Time), Bluetooth Low Energy (BLE), ultra-wideband (UWB), LiDAR, AI-powered dead reckoning, and even quantum sensors are poised to redefine how we understand and interact with location data.

Let’s dive deep into the forces reshaping the landscape of location intelligence.

The Cracks in GPS

GPS has served us well, but it was never designed for the demands of the modern digital economy. Originally built by the U.S. Department of Defense in the 1970s, GPS delivers global coverage by triangulating signals from a constellation of satellites. While this is effective in open skies, GPS performance drops significantly in dense cities, underground, or indoors—places where more and more people live, work, and travel.

“GPS is the foundation of our digital way of life, but it’s increasingly vulnerable—both from physical limitations and geopolitical tensions around satellite networks.”— Dr. Moriba Jah, Aerospace Engineer

The vulnerabilities are many: signal jamming, spoofing, multipath errors, and delays due to atmospheric interference. GPS typically has an accuracy of around 5 meters outdoors, and much worse indoors—far from sufficient for applications like autonomous vehicles, augmented reality (AR), or precision robotics.

The Rise of Hybrid Location Systems

The future of location data lies in hybrid systems—networks of complementary technologies that deliver higher accuracy, better reliability, and richer context.

1. Wi-Fi RTT (Round Trip Time)

Introduced in the IEEE 802.11mc standard, Wi-Fi RTT allows devices to calculate their distance from nearby Wi-Fi access points by measuring how long signals take to bounce back. Unlike traditional Wi-Fi positioning (based on signal strength), RTT offers sub-meter accuracy—ideal for indoor navigation.

Google has implemented Wi-Fi RTT in Android, and companies like Cisco and Aruba are building compatible access points.

Use Case: Indoor wayfinding in hospitals, shopping malls, or airports.

2. Bluetooth Low Energy (BLE) Beacons

BLE beacons (like Apple’s iBeacon and Google’s Eddystone) are a cost-effective way to enable proximity-based experiences indoors. While BLE isn’t extremely precise on its own, it becomes powerful when layered with other data.

“Think of BLE as the ‘breadcrumb trail’ of indoor environments. It won’t give you GPS-level data, but it tells you where someone has been and when.”— Martin Hjelm, VP of IoT Strategy, Kontakt.io

Use Case: Retail analytics, event attendance tracking, museum tours.

3. Ultra-Wideband (UWB)

UWB uses ultra-short pulses across a wide frequency spectrum, enabling centimetre-level accuracy with excellent resistance to interference.

Devices like the iPhone (U1 chip) and Samsung Galaxy already support UWB, and it’s gaining popularity in logistics, smart home automation, and AR navigation.

Why it matters: Perfect for precision tracking in tight or busy spaces like warehouses and factories.

4. LiDAR + Computer Vision

LiDAR (Light Detection and Ranging) systems use lasers to scan surroundings and create real-time 3D maps. When combined with AI and computer vision, devices can gain a rich understanding of their environment.

“LiDAR transforms the idea of location from ‘where am I?’ to ‘what’s around me, and how can I move safely through it?’”— Helen Greiner, Co-founder of iRobot

Already used in autonomous cars, drones, and iPhones, LiDAR gives machines context-aware navigation abilities.

5. AI-Powered Dead Reckoning

Dead reckoning estimates your position based on your last known location and motion sensors (gyroscopes, accelerometers, magnetometers). AI significantly enhances the accuracy of this method by learning typical movement patterns.

Use Case: Navigating underground tunnels, subways, or large parking structures where GPS fails.

Bonus: Google Maps’ AR mode uses dead reckoning + visual cues to help users in urban environments.

6. Quantum Positioning Systems (QPS)

Still in development, quantum sensors can measure fundamental physical forces like acceleration and gravity, enabling ultra-precise navigation without any external signals—even in GPS-denied environments.

“In a GPS-denied world—whether due to military conflict, natural disaster, or space warfare—quantum positioning could be the fallback.”— Dr. Chris Baker, Professor, University College London

Though expensive today, QPS may become the gold standard for military, aviation, and critical infrastructure applications by 2030.

📊 BONUS CHART: Location Tech Comparison Table

Technology	Accuracy	Best Use Case	Limitations
GPS	~5 meters	Outdoor navigation	Fails indoors, urban canyons
Wi-Fi RTT	<1 meter	Indoor navigation	Needs compatible routers
BLE Beacons	1-3 meters	Proximity marketing	Not very precise
UWB	<10 cm	AR, industrial automation	Cost, limited device support
LiDAR + AI	Contextual	Robotics, AR	Requires line of sight
Quantum Sensors	Sub-cm (est.)	Military, GPS-denied zones	Expensive, still in the early stages

The Role of AI and Big Data in Location Data

Location data is transforming from static coordinates into dynamic behavioural insights. Thanks to AI and big data analytics, industries are tapping into location intelligence for decision-making and optimization.

Examples in Action:

• Smart Cities: Optimize traffic, reduce energy consumption, and enhance emergency response.

• Retail: Track customer movement and optimize layouts based on heatmaps.

• Healthcare: Streamline hospital logistics and enable contact tracing during pandemics.

“The future isn’t just about knowing where something is, but understanding why it’s there, how long it stays, and what it means in context.”— Dr. Sarah Williams, MIT Civic Data Design Lab

Privacy, Ethics & Regulation

As location data becomes more granular and pervasive, privacy concerns grow. Regulations like GDPR (Europe) and CCPA (California) enforce stricter rules, but questions remain:

• Is inferred location data (from apps, Wi-Fi, etc.) covered by current laws?

• How do companies ensure consent and transparency?

• What about anonymization and data retention?

“Just because you’re not tracking a person by GPS doesn’t mean you’re not tracking them.”— Eva Galperin, Director of Cybersecurity, EFF

Companies need to prioritize ethics and transparency as location data becomes central to digital experiences.

Looking Ahead: Location Intelligence in 2030

Here’s what we might expect by the end of the decade:

• 📍 Sub-centimetre location accuracy

• 🔍 Context-aware and behaviour-driven location insights

• 🧠 AI-powered movement prediction

• 🔐 Privacy-first frameworks

• 📡 Standardized and open location infrastructure

• 🌐 Hybrid indoor-outdoor seamless navigation

Conclusion

As GPS reaches its limits, a rich ecosystem of next-generation technologies is stepping in to enhance location data, offering precision, context, and resilience. Whether it’s navigating a warehouse robot or enhancing AR experiences on your smartphone, the future of location data is multidimensional and deeply intelligent.

We’re moving beyond the map. In the words of Wired co-founder Kevin Kelly:

“The future happens when all the pieces click together—not one breakthrough, but the accumulation of many small shifts.”

Those shifts are already happening—beneath our feet, in our pockets, and across our cities.

Credit:

• IEEE 802.11mc Standard - https://ieeexplore.ieee.org

• Google Wi-Fi RTT Developer Guide - https://developer.android.com/guide/topics/connectivity/wifi-rtt

• Apple Ultra-Wideband (U1 chip) - https://support.apple.com

• Civic Data Design Lab, MIT - https://civicdatadesignlab.mit.edu/

• European GNSS Agency (GSA) Reports - https://www.euspa.europa.eu

• Electronic Frontier Foundation on Location Privacy - https://www.eff.org/issues/location-privacy