Drones & Mapping – A Match Made in Heaven?

Drones and the Location & Navigation industry could be a match made in Mapping heaven.

Datumate, a drone company from Israel (yes, where else) has rolled out drones for surveying and construction use, but this has got us thinking, why not drones for the L&N industry, particularly in Mapping?

The possibilities seem endless:

  • Quick, timely and possibly even automated map updates
  • Transcending physical obstacles and geographical challenges
  • Cost and resource efficient, compared to the existing methods of data collection

From Datumate’s existing product offerings, all this seems very plausible – Datumate’s drones and software app are already able to make precision calculations and generate high quality mapping outputs, while their handlers monitor and control progress from tablets.

Will this be the next big ‘disruption’ to the L&N industry, when a new mapping company’s flight of drones take to the skies? We are already thinking if this wil lower the barriers of entry to the prohibitively expensive Mapping industry dominated by Google, Apple and to a lesser extent HERE and TomTom.

Cybersecurity – as relevant as ever

Surely, the provision of security must count as one of the oldest professions in the world, ever since men formed and lived together in societies, sometimes harmoniously, oftentimes not.

As human societies move from the humble stone wheel to sophisticated autonomous vehicles, cyber-security has emerged as one of the biggest concerns for companies involved, according to a survey by insurer Munich Re.

This risk potentially includes the hacking of the vehicle’s information systems, as well as the failure of smart road infrastructure.

This is a new risk factor for for automobiles as we head towards increasingly connected cloud-based systems – what does not change is that the need for security and secured systems is as relevant as before.

The Philosophical Self-Driving Car

Besides the practical issues of developing sensors and maps,  a recent WIRED article poses an interesting, and perhaps under-thought of aspect of self-driving cars / autonomous vehicles – what kind of ethical decisions will they make, when something goes wrong on the road? (This, trust us, inevitably will happen)

So what happens if an autonomous vehicle is faced with a dangerous situation on the roads? Who decides? How does it decide? Will it make ethical (sacrifice the occupant to save a crowd of pedestrians), or selfish decisions (kill the pedestrians to save the occupant)? (We are already getting ahead of ourselves here and assuming the autonomous vehicle will be an adherent of J.S. Mill’s utilitarianism)

The brief answer, so far, is that the autonomous vehicle’s decision-making system will be something like what  Google has – big data capabilities discerns patterns in historical/past and available crowd behaviour, learns from them, and chooses the best possible outcome. In the first place, autonomous vehicles will have reduced the need for such ethical dilemmas, as they don’t get distracted, don’t drink, and don’t text while driving – very much unlike humans.

In two words -Machine learning, which will be far more effective than human learning.

We have to say that this does seem to give Google, with their advanced search algorithms and tremendous big data capabilities, a big edge in the autonomous car race. It is also worth noting that Google was the maker behind AlphaGo, the go-playing AI that defeated South Korean grandmaster Lee Sedol at a game that AlphaGo taught itself to play by essentially mining data, playing against itself, and defeating its creators not long after that.

Ultimately, what we have posed are hypothethical, but nevertheless, important questions, which highlight the plethora of issues that pioneering developers of the autonomous car will have to grapple with. They will have their hands full imagining possible black swan events and developing contingencies beyond just working on a product.

Apple’s new Map Office in India

India has a booming IT sector which has always been attractive to large foreign investments, with its depth of talent, cost advantages, English proficiency and recent investments in infrastructure.

Apple is the latest to be drawn to Prime Minister Modi’s new, open-for-business India. But what else does this new Apple Maps venture in Hyderabad, opened by Tim Cook himself, tell us about the state of the Location & Navigation industry?

First – Apple has put its money where its mouth is – Apple is serious about its Maps Division, and intends to compete head-on with Google on location data and maps; or at least, to keep its iOS users (and their valuable data) to itself.

Second – the potential staff count of 4,000 shows that Mapping requires some serious investment, and a lot of hard work. It is an industry with high barriers to entry, and will probably remain dominated by a couple of big players with deep pockets and the ability to develop and maintain their own maps: Google, HERE, Apple, TomTom.

Third – India has the potential to be a core Location & Navigation sub-contracting hub, due to the advantages described above. Already, Micello’s ‘Map Factories’ in India churn out indoor maps by the thousands, which are then sold on to other platforms. Domestic mapping start-up, MapMyIndia has also gone from strength to strength, giving us a glimpse of the depth of industry resources available in India. HERE, Google and now Apple all have large research facilities dealing with mapmaking in India, and over time, this will help breed a world-class Location & Navigation industry ecosystem, train talent, and spawn an entire value-chain of support services. Who knows, one day, the next big Location & Navigation player may just come from a couple of ex-HERE/Google/Apple employees in India.


Taming the great indoo.rs

Having had some experience at Indoor Mapping, we can definitely see the potential of this technology (especially at large shopping malls and airports, and for the visually-impaired community) – and how difficult creating these indoor maps actually is.

Aside from deploying beacons, which can be costly and time-consuming, the only way is to use radio signals (usually piggybacking on existing WiFi networks, although Bluetooth is another feasible option) to position a smartphone indoors. The catch? The location has to be ‘radio-fingerprinted’ first – this involves a team going on the ground to ‘fingerprint’ the unique WiFi or Bluetooth signal overlaps of the venue.

Needless to say, for large indoor venues, this is going to take time, and effort.

So what caught our attention recently is Austria-based indoo.rs’s SLAM algorithm, which promises to shorten this process by calculating and extrapolating the fingerprint data gathered from a single walk through.

While it certainly sounds tempting and promises relief to our sore legs, the accuracy of this new SLAM engine remains to be seen, even though indoo.rs has claimed that it is comparable to a comprehensive on-site ‘fingerprinting’. But given the rate indoors positioning technology is improving, we won’t be surprised if we don’t have to spend days and suffer sore knees at a venue to generate a good map anymore.

Self-driving car by 2020

Going by most auto manufacturers, self-driving cars will hit the roads by 2020 – a mere 4 years from now, with critical mass being achieved circa 2025.

Car makers, of course, will want to be at the front of this curve, or risk becoming left out altogether in the brave new world of automated driving. Who will be the leader of this new pack? The crown will be passed on again to a new usurper, as it did from America’s once-mighty auto manufacturers (the motorcar was, afterall, an American invention), to the Japanese in the 1980s, who with their leaner and more agile manufacturing processes, took the world by storm.

We are getting much closer to finding out. Now, one of the final pieces of the puzzle of fully Automated Driving seems to have come in place – an affordable radar sensor for positioning the vehicle accurately on roads. Make no mistake – the technology is nothing new, but what is revolutionary here is that a Sunnyvale, California company, Quanergys, have revealed that they are able to manufacture a solid-state LiDAR for $250 a unit – a game changer, when this technology was previously confined to expensive testing and mapping vehicles, such as Google’s now (in)famous mapping fleet.

Are we looking at a scenario for automated driving where, like the smartphone, costs came down dramatically, while adoption rates and performance shot up exponentially in a very short period of time?

Will the Americans reclaim the lead again in automotive manufacturing from the Japanese? One thing for sure – we are right on the brink of finding out.

Big Data

In recent years, we’ve seen the increasing shift towards cloud computing models, and the unstoppable rise of the smartphones – our devices have become, almost paradoxically, both increasingly mobile and increasingly connected (i.e. they need to be able to talk to – ‘sync’ – with each other in real-time).

But just what does this mean for Location and Navigation industry players?

It’s too easy to forget that a key dimension of data is geographical – in other words, location is a key part of data, especially real-time location. When correlated with other data such as user profiles, demographics and consumption patterns, it is a veritable treasure trove of data for businesses and advertisers.

Major Location and Navigation players such as Google, HERE and Apple have long ago realised the value of geographical data, harnessed by check-ins, free maps, and location tags.

And this is the reason why Indoor Mapping – where most of our modern day consumers spend their lives and make their purchasing decisions –  will be one hugely valuable enterprise.