September 1, 1983: Korean Air Lines Flight 007 (KAL007), which was a scheduled flight from New York City to Seoul via Anchorage, Alaska, strayed into the Soviet airspace. What followed was profoundly tragic and led to the escalation of tension between the two Cold War era superpowers. The plane was shot down by a Soviet Su-15 interceptor, killing all 269 passengers and crew-members on board.
For years, theories were floated around how the tragedy could have been averted. One wonders how things could have been a lot different if the pilot had access to GPS and location technology. Soon after the incident, then US President Ronald Reagan offered to let all civilian commercial aircraft use the GPS system once it was fully operational.
The availability of location and positioning can actually be a matter of life and death in certain situations. What we take for granted today was once a defense-purpose technology, with limited civilian applications. The mainstreaming of location and positioning not only ushered a technological revolution but also paved the way for an interconnected world driven by digitalization and a confluence of technologies.
With smartphones in every hand leading to exponential growth in location data, we are fast heading towards a geo-aware world, which is the next step in the path of digitalization.
In a geo-aware world, location would underpin not only the new innovations but would also be the golden thread interlinking new features. It would serve as an enabler, a pivot, as well as an interface. “A geo-aware world is one where instead of people, drones are doing the deliveries; where instead of consumers driving, they are sitting at the back, sleeping, and the cars are driving themselves. In short, it is a world where all sensors are geo-aware and where cities are aware of what’s going on,” explains Kanwar Chadha, Executive Chairman, Hubble Connect and Founder, SIRF & INOVI.
Location Intelligence: Empowering Businesses
Location analytics is a means of combining location data with business data/processes in order to draw meaningful insights, discover relationships between various factors and identify trends. It has a wide range of application — from rendering basic features such as map-based visualization to enabling complex analytics for scenario analysis. Location analytics solutions and platforms are also being used to create services based on the real-time movement of objects.
With the proliferation of mapping as an essential UI (user interface) and the ubiquity of location, the need for location intelligence (LI) is more than ever. It enables the integration of various data feeds to build better experiences and derive new insights for users. With the application of location intelligence, visualizations can be created that help convey the desired information in a lucid manner. After all, a picture speaks a thousand words.
The LI industry market has grown from nearly $9 billion in 2014 to around $22 billion in 2018, and is expected to nearly double by 2022, according to the Location Industry Market Report published by Geospatial Media and Communications in April.
Recently, Salesforce, one of the world’s top CRM (customer relationship management) companies, acquired MapAnything, a pioneer in location-based intelligence software. The development was indicative of a bigger trend — incorporation of location intelligence in business processes.
“The addition of MapAnything to Salesforce will help the world’s leading brands accurately plan: how many people they need, where to put them, how to make them as productive as possible, how to track what’s being done in real time and what they can learn to improve going forward,” according to Jon Stewart, CEO and Co-Founder, MapAnything.
Location intelligence also provides users and organizations with a robust framework for analyzing and managing geospatial data. Analyzing disparate data sources, finding commonality between them and then seamlessly bringing them together through a common interface is possible only with the help of location intelligence.
Location-based Services: Facilities at Your Fingertips
Be it hiring a cab, searching for a good Italian restaurant in your city, ordering food through a smartphone app, or getting discount offers at the nearest mart, one is often left wondering how technology is progressing and making our lives easier and simpler. The above-mentioned services, which are now part of the daily lives of millions across the globe, are essentially location-based services.
According to Gil Elbaz, Founder and CEO, Factual, location is powering smarter digital products, digital marketing, and online and offline business decisions. “Our world is now mobile, computing is everywhere, and the power of location is changing everything — the way we get around, the way we interact with brands, the way we solve problems and the way we discover new services and access information,” he says.
With the advent of digitalization and companies relying on highly accurate data for delivering “best services”, the utility of location in businesses has grown manifold and is expected to grow even further, leading to the age of automation. The location-based services (LBS) market is projected to reach $68.85 billion by 2023, at a compound annual growth rate (CAGR) of 25.4%.
GIS and Location Intelligence: The Twain Shall Meet
Geographic Information System (GIS) has been in use for several decades for delivering spatial analytics and geospatial data-based insights, while location intelligence is a comparatively new phenomenon. Despite their similarities and map-based usage spectrum, GIS and location intelligence industries have grown and stayed independent of each other. However, as their integration with business data deepens, and the industry players begin to focus on developing solutions, the convergence of GIS and location intelligence has started taking shape, according to the Location Intelligence Market Report.
Location analytics solutions usually are not designed for handling heavy spatial data. Their main focus is integrating business and location data with a map-based context. Most of the location analytics solutions offer a plug-and-play level to deliver visualization, analytics, resource and workflow management. Unlike GIS solutions, which have the ability to run in-depth queries on multiple geographic and non-geographic attributes, location analytics solutions are specifically meant for spatially referred analytics of regular business and operations data to derive intelligence on nearly real-time basis.
“Increasing amount of location data is enabling faster decision-making. However, we need more cohesiveness within the geospatial industry to grasp vast opportunities unveiled by the digital revolution,” says Alain De Taeye, Member, Management Board, TomTom.
Drones, autonomous vehicles, Internet of Things, indoor positioning, digital twins, all collect or rely on location information. Geospatial data can be harnessed for extracting valuable features that are required for creating and training new models. Location intelligence, in this case, provides a smart framework that helps understand input, output, roadmap, action plan and discrepancy, if any. Location intelligence also powers geospatial data in a Blockchain system to ensure fairness and transparency. Be it drones, IoT or Digital Twin, all of these require location intelligence.
“The next phase of growth for the geospatial industry, where it would see mainstreaming, would require ‘impact validation’ of using location intelligence. Customers would need to know how this technology is being effective for their businesses,” says Sunil Kumar, CEO, GroundTruth.
Elbaz also believes that location intelligence would lead to new innovations in the geospatial industry and open new avenues for growth and diversification. “The geospatial industry would see well-established vendors come together with newer startups to focus on emerging categories and use cases. In the end, all industries stand to benefit from comprehensive location data and intelligence, and there are many fruitful partnerships that would be built,” he adds.
The Drivers: New Advancements and Emerging Technologies
The location intelligence industry is being driven not just by the growing demand from its users, but also by new advancements in other technologies that ultimately enable it to offer better propositions to its current and potential customers.
Emerging technologies like artificial intelligence, autonomous systems and IoT are expected to drastically transform location analytics. The arrival of 5G would be another game changer for location data and foster rapid innovations. This would enable not only an increase in location awareness but also location becoming a pillar of most technological processes.
Rise of Indoor Positioning
In a world of increasing customer intimacy, venue-based marketing strategies and increasing demand for location-based services and application by smartphone users, the rise of indoor positioning services (IPS) is but obvious.
Indoor Mapping is not possible without a highly precise location. It combines the power of GPS and precise mapping to the place where human beings spend 70% of their time – indoors. According to the United States’ National Geospatial Advisory Committee (NGAC), indoor positioning services provide the ability for real-time tracking of location information on people or objects indoor with the help of sensory information from automated devices.
The global indoor location market is estimated to touch $40.99 billion by 2022 from $5.22 billion in 2016 at a compound annual growth rate (CAGR) of 42.0% during the forecast period. Moreover, retailers are expected to spend $2.4 billion annually on beacons and asset tracking in 2020. It’s no surprise then that there are hundreds of startups competing for visibility in the emerging indoor location and proximity marketing arena.
Indoor positioning can be broadly classified into: magnetic positioning, SLAM, radio waves, mobile sensors and RFID. However, it must be mentioned that there is no standard way to build an IPS.
The wide availability of sensor-rich mobiles has boosted the possibility for accuracy of indoor positioning services. In addition to sensors like GPS (which usually doesn’t work indoors but if there is satellite signal the smartphone can determine its position) and Bluetooth, modern-day smartphones are equipped with a variety of sensors like barometer, acceleration sensor, gyroscope, mobile phone antenna, Near Field Communication (NFC is a radio standard with a maximum range of 10 cm and is being used for contact-free payment by AndroidPay and ApplePay) and camera (the smartphone cameras receive visible light communication signals and can be used for virtual reality applications).
“Location-aware AI and deep learning have the advantage of drawing on features at or near that location or a history of events there,” underlines Javier De La Torre, Founder and Chief Strategy Officer, CARTO. Pointing out that IoT is providing countless measurements associated with location, he adds that by combining these with other relevant data sources, data scientists are helping cities, businesses and autonomous vehicles make better and more informed decisions.
Using advanced analytics methods and smart optimization for vastly improving anything from communication systems to logistics to the myriad applications of Blockchain and AI that will immensely benefit the consumers, location intelligence today has become a critical component in workflows.
Further advances in location technology would lead to storing and analysis of reams of data, new methodologies, more sophisticated predictive models and visualization tools. A combination of all of these would provide unprecedented insights and change the course of industries as well as societies.
The Future: Autonomous Mobility and Location
Location would be at the heart of the automotive industry, not just for ride-hailing services or navigation, but also for a number of other reasons. Autonomous vehicles would be requiring real-time mapping that is based on precise location.
Autonomous vehicles will depend on a data-driven mapping system that HERE calls a “self-heal system”. The map would update real-time information and include the latest information about the surroundings based on the car’s location. For instance, if there is an alert about a roadblock ahead, or about poor road condition in another part of the town, maps would update themselves real-time by gathering and analyzing information from a variety of crowdsourced updates
“If you think about a six ton car running at 60 miles per hour, you better have good communication with it and you better have good location for it. Otherwise it’s a disaster waiting to happen,” says Elbaz.
According to Ganesh Pattabiraman, CEO of NextNav, “Location is one of the key pieces of information that is required to be reliable for a car to drive down a freeway, a drone to fly, or a mobile phone to interact with the world around. So, location industry is going to be one of the key pillars on which the future of autonomous world will be built.” NextNav is developing something called Metropolitan Beacon System (MBS), a wide area location and timing technology designed to provide services in areas where GPS signals are not available.
The Challenges: Data Accuracy and Integration
In an automated world, where most processes would hinge on real-time availability of data, even a lag of a few nanoseconds could lead to big blunders or a colossal loss of revenue for an organization. Real-time geospatial information and visualization of location would be crucial for multiple reasons in the future.
“The other important enabler that is going to be super important going forward is the ability to handle real-time event flow — receiving real-time data streams from a variety of sources, sensors, IoT devices — and operating on those streams in real time to take action and deliver events to other systems,” explains Sandeep Singhal, Director, Cloud Storage, Google. Today, in many cases, merging multiple streams together in order to recognize information or patterns is of utmost importance. In some sense, the integration of multiple partners and providers will happen not just at the physical data level, but also at the advanced stream level.
However, the demands and expectations of the consumers are fast outpacing the technological capability of the industry. The foremost problem is the accuracy of location data, the ability to use location reliably, whether it is in automated map-making, or day-to-day end-user applications.
Mike Davie, CEO and Founder, Quadrant, paints a very realistic picture when he says that a city government may purchase location data surrounding the movement of its citizens and use that data to plan new bus routes, train stations, hospitals or emergency services. But if this data is wrong, then the result could be anything from wasted spending (and higher taxes) to worse crime or slower economic growth. The problem is, data accuracy and quality are rarely questioned, and rather it is the end analysis and decision-making that usually bears the brunt of the criticism when things go wrong.
One way to close this increasing gap is through real-time streaming that can be made possible by the integration of geo-data with non-spatial data. However, merging data from different sources, particularly from multiple geospatial sources, is still very difficult. “We don’t have good universal point standards for mapping information or merging information together for using the same featured language across multiple sources,” adds Singhal.
This again brings us to the original premise of standardization. Embedding geo-data and location element into other datasets requires standardization, and this is another area where the industry is lagging behind.
“Standards among geo sources enable a set of patterns, tools, capabilities for merging the data sources together. Therefore, the question is — does a customer have to go to five different vendors, get their data and figure out how to use it together, or can the industry actually support patterns and collaboration among different suppliers to deliver what is needed,” adds Singhal.
The Way Forward: Precision, Precision & Precision
The democratization of this data would provide impetus to new innovations in a number of sectors. Data scientists across the world are working on increasing the accuracy of location data and refining the data algorithms. An increase in data quality is directly linked with increased efficiency and underscores the criticality of highly precise location data.
Location accuracy is an issue that drains financial resources. One of the ways around is very high-frequency data and crosschecking whether or not a person is at the said location.
The next generation consumer is going to be a mobile entity — be it a drone, self-driving car, or an autonomous robot. “We have these hybrid entities, or humans wearing AR and you are exactly not sure what they are. These people and devices need context and information in order to do their job well,” explains Elbaz.
Location intelligence is undoubtedly the next stage of evolution and offers a lot of prospects not only for the location and geospatial segments, but also for every industry that will be affected by automation.
Location would be the fulcrum of a geo-aware world. Figuratively speaking, it will be the axle connecting the various wheels in the streetcar called automation. Advancements in location technology would fundamentally alter not only the way individuals interact with technology, but also create a new paradigm where the primary users of location technology would be machines and platforms.