Category Archives: Drones/UAVs

Humanitarian Robotics: The $15 Billion Question?

The International Community spends around $25 Billion per year to provide life saving assistance to people devastated by wars and natural disasters. According to the United Nations, this is $15 Billion short of what is urgently needed; that’s $15 Billion short every year. So how do we double the impact of humanitarian efforts and do so at half the cost?

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Perhaps one way to deal with this stunning 40% gap in funding is to scale the positive impact of the aid industry. How? By radically increasing the efficiency (time-savings) and productivity (cost-savings) of humanitarian efforts. This is where Artificial Intelligence (AI) and Autonomous Robotics come in. The World Economic Forum refers to this powerful new combination as the 4th Industrial Revolution. Amazon, Facebook, Google and other Top 100 Fortune companies are powering this revolution with billions of dollars in R&D. So whether we like it or not, the robotics arms race will impact the humanitarian industry just like it is impacting other industries: through radical gains in efficiency & productivity.

Take Amazon, for example. The company uses some 30,000 Kiva robots in its warehouses across the globe (pictured below). These ground-based, terrestrial robotics solutions have already reduced Amazon’s operating expenses by no less than 20%. And each new warehouse that integrates these self-driving robots will save the company around $22 million in fulfillment expenses alone. According to Deutsche Bank, “Bringing the Kivas to the 100 or so distribution centers that still haven’t implemented the tech would save Amazon a further $2.5 billion.” As is well known, the company is also experimenting with aerial robotics (drones). A recent study by PwC (PDF) notes that “the labor costs and services that can be replaced by the use of these devices account for about $127 billion today, and that the main sectors that will be affected are infrastructure, agriculture, and transportation.” Meanwhile, Walmart and others are finally starting to enter the robotics arms race. The former is using ground-based robots to ship apparel and is actively exploring the use of aerial robotics to “photograph ware-house shelves as part of an effort to reduce the time it takes to catalogue inventory.”

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What makes this new industrial revolution different from those that preceded it is the fundamental shift from manually controlled technologies—a world we’re all very familiar with—to a world powered by increasingly intelligent and autonomous systems—an entirely different kind of world. One might describe this as a shift towards extreme automation. And whether extreme automation powers aerial robotics, terrestrial robotics or maritime robots (pictured below) is besides the point. The disruption here is the one-way shift towards increasingly intelligent and autonomous systems.

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Why does this fundamental shift matter to those of us working in humanitarian aid? For at least two reasons: the collection of humanitarian information and the transportation of humanitarian cargo. Whether we like it or not, the rise of increasingly autonomous systems will impact both the way we collect data and transport cargo by making these processes faster, safer and more cost-effective. Naturally, this won’t happen overnight: disruption is a process.

Humanitarian organizations cannot stop the 4th Industrial Revolution. But they can apply their humanitarian principles and ideals to inform how autonomous robotics are used in humanitarian contexts. Take the importance of localizing aid, for example, a priority that gained unanimous support at the recent World Humanitarian Summit. If we apply this priority to humanitarian robotics, the question becomes: how can access to appropriate robotics solutions be localized so that local partners can double the positive impact of their own humanitarian efforts? In other words, how do we democratize the 4th Industrial Revolution? Doing so may be an important step towards closing the $15 billion gap. It could render the humanitarian industry more efficient and productive while localizing aid and creating local jobs in new industries.

This is What Happens When You Send Flying Robots to Nepal

In September 2015, we were invited by our partner Kathmandu University to provide them and other key stakeholders with professional hands-on training to help them scale the positive impact of their humanitarian efforts following the devastating earthquakes. More specifically, our partners were looking to get trained on how to use aerial robotics solutions (drones) safely and effectively to support their disaster risk reduction and early recovery efforts. So we co-created Kathmandu Flying Labs to ensure the long-term sustainability of our capacity building efforts. Kathmandu Flying Labs is kindly hosted by our lead partner, Kathmandu University (KU). This is already well known. What is hardly known, however, is what happened after we left the country.

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Our Flying Labs are local innovation labs used to transfer both relevant skills and appropriate robotics solutions sustainably to outstanding local partners who need these the most. The co-creation of these Flying Labs include both joint training and applied projects customized to meet the specific needs & priorities of our local partners. In Nepal, we provided both KU and Kathmandu Living Labs (KLL) with the professional hands-on training they requested. What’s more, thanks to our Technology Partner DJI, we were able to transfer 10 DJI Phantoms (aerial robotics solutions) to our Nepali partners (6 to KU and 4 to KLL). In addition, thanks to another Technology Partner, Pix4D, we provided both KU and KLL with free licenses of the Pix4D software and relevant training so they could easily process and analyze the imagery they captured using their DJI platforms. Finally, we carried out joint aerial surveys of Panga, one of the towns hardest-hit by the 2015 Earthquake. Joint projects are an integral element of our capacity building efforts. These projects serve to reinforce the training and enable our local partners to create immediate added value using aerial robotics. This important phase of Kathmandu Flying Labs is already well documented.

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What is less known, however, is what KU did with the technology and software after we left Nepal. Indeed, the results of this next phase of the Flying Labs process (during which we provide remote support as needed) has not been shared widely, until now. KU’s first order of business was to actually finish the joint project we had started with them in Panga. It turns out that our original aerial surveys there were actually incomplete, as denoted by the red circle below.

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But because we had taken the time to train our partners and transfer both our skills and the robotics technologies, the outstanding team at KU’s School of Engineering returned to Panga to get the job done without needing any further assistance from us at WeRobotics. They filled the gap:

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The KU team didn’t stop there. They carried out a detailed aerial survey of a nearby hospital to create the 3D model below (at the hospital’s request). They also created detailed 3D models of the university and a nearby temple that had been partially damaged by the 2015 earthquakes. Furthermore, they carried out additional disaster damage assessments in Manekharka and Sindhupalchowk, again entirely on their own.

Yesterday, KU kindly told us about their collaboration with the World Wildlife Fund (WWF). Together, they are conducting a study to determine the ecological flow of Kaligandaki river, one of the largest rivers in Nepal. According to KU, the river’s ecosystem is particularly “complex as it includes aquatic invertebrates, flora, vertebrates, hydrology, geo-morphology, hydraulics, sociology-cultural and livelihood aspects.” The Associate Dean at KU’s School of Engineering wrote “We are deploying both traditional and modern technology to get the information from ground including UAVs. In this case we are using the DJI Phantoms,” which “reduced largely our field investigation time. The results are interesting and promising.” I look forward to sharing these results in a future blog post.

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Lastly, KU’s Engineering Department has integrated the use of the robotics platforms directly into their courses, enabling Geomatics Engineering students to use the robots as part of their end-of-semester projects. In sum, KU has done truly outstanding work following our capacity building efforts and deserve extensive praise. (Alas, it seems that KLL has made little to no use of the aerial technologies or the software since our training 10 months ago).

Several months after the training in Nepal, we were approached by a British company that needed aerial surveys of specific areas for a project that the Nepal Government had contracted them to carry out. So they wanted to hire us for this project. We proposed instead that they hire our partners at Kathmandu Flying Labs since the latter are more than capable to carry out the surveys themselves. In other words, we actively drive business opportunities to Flying Labs partners. Helping to create local jobs and local businesses around robotics as a service is one of our key goals and the final phase of the Flying Labs framework.

So when we heard last week that USAID’s Global Development Lab was looking to hire a foreign company to carry out aerial surveys for a food security project in Nepal, we jumped on a call with USAID to let them know about the good work carried out by Kathmandu Flying Labs. We clearly communicated to our USAID colleagues that there are perfectly qualified Nepali pilots who can carry out the same aerial surveys. USAID’s Development Lab will be meeting with Kathmandu Flying Labs during their next visit in September.

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On a related note, one of the participants who we trained in September was hired soon after by Build Change to support the organization’s shelter programs by producing Digital Surface Models (DSMs) from aerial images captured using DJI platforms. More recently, we heard from another student who emailed us with the following: “I had an opportunity to participate in the Humanitarian UAV Training mission in Nepal. It’s because of this training I was able learn how to fly drones and now I can conduct aerial Survey on my own with any hardware.  I would like to thank you and your team for the knowledge transfer sessions.”

This same student (who graduated from KU) added: “The workshop that your team did last time gave us the opportunity to learn how to fly and now we are handling some professional works along with major research. My question to you is ‘How can young graduates from developing countries like ours strengthen their capacity and keep up with their passion on working with technology like UAVs […]? The immediate concern for a graduate in Nepal is a simple job where he can make some money for him and prove to his family that he has done something in return for all the investments they have been doing upon him […]’.

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This is one of several reasons why our approach at WeRobotics is not limited to scaling the positive impact of local humanitarian, development, environmental and public health projects. Our demand-driven Flying Labs model goes the extra (aeronautical) mile to deliberately create local jobs and businesses. Our Flying Labs partners want to make money off the skills and technologies they gain from WeRobotics. They want to take advantage of the new career opportunities afforded by these new AI-powered robotics solutions. And they want their efforts to be sustainable.

In Nepal, we are now interviewing the KU graduate who posed the question above because we’re looking to hire an outstanding and passionate Coordinator for Kathmandu Flying Labs. Indeed, there is much work to be done as we are returning to Nepal in coming months for three reasons: 1) Our local partners have asked us to provide them with the technology and training they need to carry out large scale mapping efforts using long-distance fixed-wing platforms; 2) A new local partner needs to create very high-resolution topographical maps of large priority areas for disaster risk reduction and planning efforts, which requires the use of a fixed-wing platform; 3) We need to meet with KU’s Business Incubation Center to explore partnership opportunities since we are keen to help incubate local businesses that offer robotics as a service in Nepal.

How to Democratize Humanitarian Robotics

Our world is experiencing an unprecedented shift from manually controlled technologies to increasingly intelligent and autonomous systems powered by artificial intelligence (AI). I believe that this radical shift in both efficiency and productivity can have significant positive social impact when it is channeled responsibly, locally and sustainably.

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This is why my team and I founded WeRobotics, the only organization fully dedicated to accelerating and scaling the positive impact of humanitarian, development and environmental projects through the appropriate use of AI-powered robotics solutions. I’m thrilled to announce that the prestigious Rockefeller Foundation shares our vision—indeed, the Foundation has just awarded WeRobotics a start-up grant to take Humanitarian Robotics to the next level. We’re excited to leverage the positive power of robotics to help build a more resilient world in line with Rockefeller’s important vision.

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Aerial Robotics (drones/UAVs) represent the first wave of robotics to impact humanitarian sectors by disrupting traditional modes of data collection and cargo delivery. Both timely data and the capacity to act on this data are integral to aid, development and environmental projects. This is why we are co-creating and co-hosting global network of “Flying Labs”; to transfer appropriate aerial robotics solutions and relevant skills to outstanding local partners in developing countries who need these the most.

Our local innovation labs also present unique opportunities for our Technology Partners—robotics companies and institutes. Indeed, our growing network of Flying Labs offer a multitude of geographical, environmental and social conditions for ethical social good projects and responsible field-testing; from high-altitude glaciers and remote archipelagos experiencing rapid climate change to dense urban environments in the tropics subject to intense flooding and endangered ecosystems facing cascading environmental risks.

The Labs also provide our Technology Partners with direct access to local knowledge, talent and markets, and in turn provide local companies and entrepreneurs with facilitated access to novel robotics solutions. In the process, our local partners become experts in different aspects of robotics, enabling them to become service providers and drive new growth through local start-up’s and companies. The Labs thus seek to offer robotics-as-a-service across multiple local sectors. As such, the Labs follow a demand-driven social entrepreneurship model designed to catalyze local businesses while nurturing learning and innovation.

Of course, there’s more to robotics than just aerial robotics. This is why we’re also exploring the use of AI-powered terrestrial and maritime robotics for data collection and cargo delivery. We’ll add these solutions to our portfolio as they become more accessible in the future. In the meantime, sincerest thanks to the Rockefeller Foundation for their trust and invaluable support. Big thanks also to our outstanding Board of Directors and to key colleagues for their essential feed-back and guidance.

Humanitarian Cargo Delivery via Aerial Robotics is Not Science Fiction (Updated)

I had the opportunity to visit Zipline’s field-testing site in San Francisco last year after the company participated in an Experts Meeting on Humanitarian UAVs (Aerial Robotics) that I co-organized at MIT. The company has finally just gone public about their good work in Rwanda, so I’m at last able to blog about it on iRevolutions. When I write “finally”, this is not meant to be a complaint; in fact, one aspect that really drew me to Zipline in the first place is the team’s genuine down-to-earth, no-hype mantra. So, I use the word finally since I now finally have public evidence to backup many conversations I’ve had with humanitarian partners on the topic of cargo delivery via aerial robotics.

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As I had signed an NDA, I was (and still am) only allowed to discuss information that is public, which was basically nothing until today. So below is a summary of what is at last publicly known about Zipline’s pioneering aerial robotics efforts in Rwanda. I’ve also added videos at the end.

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  • Zipline’s Mission: to deliver critical medical products to health centers and hospitals that are either difficult or impossible to reach via traditional modes of transportation
  • Zipline Fleet: 15 aerial robotics platforms (UAVs) in Rwanda.
  • Aerial Robotics platform: Fixed-wing.
  • Weight of each platform: 10-kg.
  • Power: Battery-operated twin-electric motors.
  • Payload capacity: up to 1.5kg.
  • Cargo: Blood and essential medicines (small vials) to begin with. Eventually cargo will extend to lifesaving vaccines, treatments for HIV/AIDS, malaria, tuberculosis, etc.
  • Range: Up to 120 km.
  • Flight Plans: Pre-programmed and monitored on the ground via tablets. Individual plans are stored on SIM cards.

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  • Flight Navigation: GPS using the country’s cellular network.
  • Launch Mechanism: Via catapult.
  • Maximum Speed: Around 100 km/hour.
  • Landings: Zipline’s aerial robot does not require a runway.
  • Delivery Mechanism: Fully autonomous, low altitude drop via simple paper parachute. Onboard computers determine appropriate parameters (taking into account winds, etc) to ensure that the cargo accurately lands on it’s dedicated delivery site called a “mailbox”.
  • Delivery Sites: Dedicated drop sites at 21 health facilities that can carry out blood transfusions. These cover more than half of Rwanda.

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  • Takeoff Sites: Modified shipping containers located next to existing medical warehouses.
  • Delivery Time: Each cargo is delivered within 1 hour. The aerial robot takes about 1/2 hour reach a delivery site.
  • Flight Frequency: Eventually up to 150 flights per day.
  • Weather: Fixed-wings can operate in ~50km/hour winds.
  • Regulatory Approval: Direct agreements already secured with the Government of Rwanda and country’s Civil Aviation Authority.

Sources:

Think Global, Fly Local: The Future of Aerial Robotics for Disaster Response

First responders during disasters are not the United Nations or the Red Cross. The real first responders, by definition, are the local communities; always have been, always will be. So the question is: can robotics empower local communities to respond and recover both faster and better? I believe the answer is Yes.

But lets look at the alternative. As we’ve seen from recent disasters, the majority of teams that deploy with aerial robotics (UAVs) do so from the US, Europe and Australia. The mobilization costs involved in flying a professional team across the world—not to mention their robotics equipment—is not insignificant. And this doesn’t even include the hotel costs for a multi-person team over the course of a mission. When you factor in these costs on top of the consulting fees owed to professional international robotics teams, then of course the use of aerial robotics versus space robotics (satellites) becomes harder to justify.

There is also an important time factor. The time it takes for international teams to obtain the necessary export/import permits and customs clearance can be highly unpredictable. More than one international UAV team that (self) deployed to Nepal after the tragic 2015 Earthquake had their robotics platforms held up in customs for days. And of course there’s the question of getting regulatory approval for robotics flights. Lastly, international teams (especially companies and start-up’s) may have little to no prior experience working in the country they’re deploying to; they may not know the culture or speak the language. This too creates friction and can slow down a humanitarian robotics mission.

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What if you had fully trained teams on the ground already? Not an international team, but a local expert robotics team that obviously speaks the local language, understands local customs and already has a relationship with the country’s Civil Aviation Authority. A local team does not need to waste time with export/import permits or customs clearance; doesn’t need expensive international flights or weeks’ worth of hotel accommodations. They’re on site, and ready to deploy at a moment’s notice. Not only would this response be faster, it would be orders of magnitudes cheaper and more sustainable to carry through to the recovery and reconstruction phase.

In sum, we need to co-create local Flying Labs with local partners including universities, NGOs, companies and government partners. Not only would these Labs be far more agile and rapid vis-a-vis disaster response efforts, they would also be far more sustainable and their impact more scalable than deploying international robotics teams. This is one of the main reasons why my team and I at WeRobotics are looking to co-create and connect a number of Flying Labs in disaster prone countries across Asia, Africa and Latin America. With these Flying Labs in place, the cost of rapidly acquiring high quality aerial imagery will fall significantly. Think Global, Fly Local.

Aerial Robotics for Payload Delivery in Developing Countries: Open Questions

Should developing countries seek to manufacture their own robotics solutions in order to establish payload delivery services? What business models make the most sense to sustain these services? Do decision-support tools already exist to determine which delivery routes are best served by aerial robots (drones) rather than traditional systems (such as motorbikes)? And what mechanisms should be in place to ensure that the impact of robotics solutions on local employment is one of net job creation rather than job loss?

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There are some of the questions I’ve been thinking about and discussing with various colleagues over the past year vis-a-vis humanitarian applications. So let me take the first 2 questions and explore these further here. I’ll plan on writing a follow up post in the near future to address the other two questions.

First, should developing countries take advantage of commercial solutions that already exist to build their robotics delivery infrastructure? Or should they seek instead to manufacture these robotics platforms locally instead? The way I see it, this does not have to be an either/or situation. Developing countries can both benefit from the robust robotics technologies that already exist and take steps to manufacture their own solutions over time.

This is not a hypothetical debate. I’ve spent the past few months going back and forth with a government official in a developing country about this very question. The official is not interested in leveraging existing commercial solutions from the West. As he rightly notes, there are many bright engineers in-country who are able and willing to build these robotics solutions locally.

Here’s the rub, however, this official has no idea just how much work, time and money is needed to develop robust, reliable and safe robotics solutions. In fact, many companies in both Europe and the US have themselves completely under-estimated just how technically challenging (and very expensive) it is to develop reliable aerial robotics solutions to delivery payloads. This endeavor easily takes years and millions of dollars to have a shot at success. It is far from trivial.

The government official in question wants his country’s engineers to build these solutions locally in order to transport essential medicines and vaccines between health clinics and remote villages. Providing this service is relatively urgent because existing delivery mechanisms are slow, unreliable and at times danger-ous. So this official will have to raise a substantial amount of funds to pay local engineers to build home-grown robotics solutions and iterate accordingly. This could take years (with absolutely no guarantee of success mind you).

On the other hand, this same official could decide to welcome the use of existing commercial solutions as part of field-tests in-country. The funding for this would not have to come from the government and the platforms could be field-tested as early as this summer. Not only would this provide local engineers with the ability to learn from the tests and gain important engineering insights, they could also be hired to actually operate the cargo delivery services over the long-term, thus gaining the skills to maintain and fix the platforms. Learning by doing would give these engineers practical training that they could use to build their own home-grown solutions.

One could be even more provocative: Why invest so much time and effort in local manufacturing when in-country engineers and entrepreneurs could simply use commercial solutions that already exist to make money sooner rather than later by providing robotics as a service? We’ve seen, historically, the transition from manufacturing to service-based economies. There’s plenty of profit to be made from the latter with a lot less start-up time and capital required. And again, one strategy does not preclude the other, so why forgo both early training and business opportunities when these same opportunities could help develop and fund the local robotics industry?

Admittedly, I’m somewhat surprised by the official’s zero tolerance for the use of foreign commercial technology to improve his country’s public health services; that same official is using computers, phones, cars, televisions, etc., that are certainly not made in-country. He does not have a background in robotics, so perhaps he assumes that building robust robotics solutions is relatively easy. Simply perusing the past 2 years of crowdfunded aerial robotics projects will clearly demonstrate that most have resulted in complete failure despite raising millions of dollars. That robotics graveyard keeps growing.

But I fully respect the government official’s position even if I disagree with it. In my most recent exchange with said official, I politely re-iterated that one strategy (local manufacturing) does not preclude the other (local business opportunities around robotics as service using foreign commercial solutions). Surely, the country in question can both leverage foreign technology while also building a local manufacturing base to produce their own robotics solutions.

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Second, on business models, which models can provide sustainability by having aerial delivery services be profitable earlier rather than later? I was recently speaking to a good colleague of mine who works for a very well-respected humanitarian group about their plans to pilot the use of aerial robotics for the delivery of essential medicines. When I asked him about his organization’s business model for sustaining these delivery services, he simply said there was no model, that his humanitarian organization would simply foot the bill.

Surely we can do better. Just think how absurd it would be for a humanitarian organization to pay for their own 50 kilometer paved road to transport essential medicines by truck and decide not to recoup those major costs. You’ve paid for a perfectly good road that only gets used a few times a day by your organization. But 80% of the time there is no one else on that road. That would be absurd. Humanitarians who seek to embark on robotics delivery projects should really take the time to understand local demand for transportation services and use-cases to explore strategies to recoup part of their investments in building the aerial robotics infrastructure.

Surely remote communities who are disconnected from health services are also disconnected from access to other commodities. Of course, these local villages may not benefit from high levels of income; but I’m not suggesting that we look for high margins of return. Point is, if you’ve already purchased an aerial robot (drone) and it spends 80% of its time on the ground, then talk about a missed opportunity. Take commercial aviation as an analogy. Airlines do not make money when their planes are parked at the gate. They make money when said planes fly from point A to point B. The more they fly, the more they transport, the more they profit. So pray tell what is the point of investing in aerial robots only to have them spend most of their lives on the ground? Why not “charter” these robots for other purposes when they’re not busy flying medicines?

The fixed costs are the biggest hurdle with respect to aerial robotics, not the variable costs. Autonomous flights themselves cost virtually nothing; only 1-2 person’s time to operate the robot and swap batteries & payloads. Just like their big sisters (manually piloted aircraft), aerial robots should be spending the bulk of their time in the sky. So humanitarian organizations really ought to be thinking earlier rather than later about how to recoup part of their fixed costs by offering to transport other high-demand goods. For example, by allowing local businesses to use existing robotics aircraft and routes to transport top-up cards or SIM cards for mobile phones. What is the weight of 500 top-up or SIM cards? Around 0.5kg, which is easily transportable via aerial robot. Better yet, identify perishable commodities with a short shelf-life and allow business to fly those via aerial robot.

The business model that I’m most interested in at the moment is a “Per Flight Savings” model. One reason to introduce robotics solutions is to save on costs—variable costs in particular. Lest say that the variable cost of operating robotics solutions is 20% lower than the costs of traditional delivery mechanisms (per flight versus per drive, for example). You offer the client a 10% cost saving and pocket the other 10% as revenue. Over time, with sufficient flights (transactions) and growing demand, you break even and start to create a profit. I realize this is a hugely simplistic description; but this need not be unnecessarily complicated either.  The key will obviously be the level of demand for these transactions.

The way I see it, regardless of the business model, there will be a huge first-mover advantage in developing countries given the massive barriers to entry. Said barriers are primarily due to regulatory issues and air traffic management challenges. For example, once a robotics company manages to get regulatory approval and specific flight permissions for designated delivery routes to supply essential medicines, a second company that seeks to enter the market may face even greater barriers. Why? Because managing aerial robotics platforms from one company and segregating that airspace from manned aircraft can already be a challenge (not to mention a source of concern for Civil Aviation Authorities).

So adding new (and different types of) robots from a second company requires new communication protocols between the different robotics platforms operated by the 2 different companies. In sum, the challenges become more complex more quickly as new competitors seek entry. And for an Aviation Authority that may already be weary of flying robots, the proposal of adding a second fleet from a different company in order to increase competition around aerial deliveries may take said Authority some time to digest. Of course, if these companies can each operate in completely different parts of a given country, then technically this is an easier challenge to manage (and less anxiety provoking for authorities).

But said barriers do not only include technical (though surmountable) barriers. They also include identifying those (few?) use-cases that clearly make the most business sense to recoup one’s investments earlier rather than later given the very high start-up fixed costs associated with developing robotics platforms. Identifying these business cases is typically not something that’s easily done remotely. A considerable amount of time and effort must be spent on-site to identify and meet possible stakeholders in order to brainstorm and discover key use-cases. And my sense is that aerial robots often need to be designed to meet a specific use-case. So even when new use-cases are identified, there may still be the need for Research and Development (R&D) to modify a given robotics platform so it can most efficiently cater to new use-cases.

There are other business models worth thinking through for related services, such as those around the provision of battery-charging services, for example. The group Mobisol has installed solar home systems on the roofs of over 40,000 households in Rwanda and Tanzania to tackle the challenge of energy poverty. Mobisol claims to already cover much of Tanzania with solar panels that are no more than 5 kilometers apart. This could enabling aerial robots (UAVs) to hop from recharging station to recharging station, an opportunity that Mobisol is already actively exploring. Practical challenges aside, this network of charging stations could lead to an interesting business model around the provision of aerial robotics services.

As the astute reader will have gathered, much of the above is simply a written transcript me thinking out load. So I’d very much welcome some intellectual company here along with constructive feedback. What am I missing? Is my logic sound? What else should I be taking into account?

A 10 Year Vision: Future Trends in Geospatial Information Management

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The United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) recently published their second edition of Future Trends in Geospatial Information Management. I blogged about the first edition here. Below are some of the excerpts I found interesting or noteworthy. The report itself is a 50-page document (PDF 7.1Mb).

  • The integration of smart technologies and efficient governance models will increase and the mantra of ‘doing more for less’ is more relevant than ever before.
  • There is an increasing tendency to bring together data from multiple sources: official statistics, geospatial information, satellite data, big data and crowdsourced data among them.
  • New data sources and new data collection technologies must be carefully applied to avoid a bias that favors countries that are wealthier and with established data infrastructures. The use of innovative tools might also favor those who have greater means to access technology, thus widening the gap between the ‘data poor’ and the ‘data rich’.
  • The paradigm of geospatial information is changing; no longer is it used just for mapping and visualization, but also for integrating with other data sources, data analytics, modeling and policy-making.
  • Our ability to create data is still, on the whole, ahead of our ability to solve complex problems by using the data.  The need to address this problem will rely on the development of both Big Data technologies and techniques (that is technologies that enable the analysis of vast quantities of information within usable and practical timeframes) and artificial intelligence (AI) or machine learning technologies that will enable the data to be processed more efficiently.
  • In the future we may expect society to make increasing use of autonomous machines and robots, thanks to a combination of aging population, 
rapid technological advancement in unmanned autonomous systems and AI, and the pure volume of data being beyond a human’s ability to process it.
  • Developments in AI are beginning to transform the way machines interact with the world. Up to now machines have mainly carried out well-defined tasks such as robotic assembly, or data analysis using pre-defined criteria, but we are moving into an age where machine learning will allow machines to interact with their environment in more flexible and adaptive ways. This is a trend we expect to 
see major growth in over the next 5 to 10 years as the technologies–and understanding of the technologies–become more widely recognized.
  • Processes based on these principles, and the learning of geospatial concepts (locational accuracy, precision, proximity etc.), can be expected to improve the interpretation of aerial and satellite imagery, by improving the accuracy with which geospatial features can be identified.
  • Tools may run persistently on continuous streams of data, alerting interested parties to new discoveries and events.  Another branch of AI that has long been of interest has been the expert system, in which the knowledge and experience of human experts 
is taught to a machine.
  • The principle of collecting data once only at the highest resolution needed, and generalizing ‘on the fly’ as required, can become reality.  Developments of augmented and virtual reality will allow humans to interact with data in new ways.
  • The future of data will not be the conflation of multiple data sources into a single new dataset, rather there will be a growth in the number of datasets that are connected and provide models to be used across the world.
  • Efforts should be devoted to integrating involuntary sensors– mobile phones, RFID sensors and so
on–which aside from their primary purpose may produce information regarding previously difficult to collect information. This leads to more real-time information being generated.
  • Many developing nations have leapfrogged in areas such as mobile communications, but the lack of core processing power may inhibit some from taking advantage of the opportunities afforded by these technologies.
  • Disaggregating data at high levels down to small area geographies. This will increase the need to evaluate and adopt alternative statistical modeling techniques to ensure that statistics can be produced at the right geographic level, whilst still maintaining the quality to allow them to be reported against.
  • The information generated through use of social media and the use of everyday devices will further reveal patterns and the prediction of behaviour. This is not a new trend, but as the use of social media 
for providing real-time information and expanded functionality increases it offers new opportunities for location based services.
  • There seems to have been
 a breakthrough from 2D to 3D information, and
 this is becoming more prevalent.

 Software already exists to process this information, and to incorporate the time information to create 4D products and services. It 
is recognized that a growth area over the next five to ten years will be the use of 4D information in a wide variety of industries.
  • 
 The temporal element is crucial to a number of applications such as emergency service response, for simulations and analytics, and the tracking of moving objects. 
 4D is particularly relevant in the context of real-time information; this has been linked to virtual reality technologies.
  • Greater coverage, quality and resolution has been achieved by the availability of both low-cost and affordable satellite systems, and unmanned aerial vehicles (UAVs). This has increased both the speed of collection and acquisition in remote areas, but also reduced the cost barriers of entry.
  • UAVs can provide real-time information to decision-makers on the ground providing, for example, information for disaster manage-ment. They are
 an invaluable tool when additional information 
is needed to improve vital decision making capabilities and such use of UAVs will increase.
  • The licensing of data in an increasingly online world is proving to be very challenging. There is a growth in organisations adopting simple machine-readable licences, but these have not resolved the issues to data. Emerging technologies such as web services and the growth of big data solutions drawn from multiple sources will continue to create challenges for the licensing of data.
  • A wider issue is the training and education of a broader community of developers and users of location-enabled content. At the same time there is a need for more automated approaches to ensuring the non-geospatial professional community get the right data at the right time. 
Investment in formal training in the use of geospatial data and its implementation is still indispensable.
  • Both ‘open’ and ‘closed’ VGI 
data play an important and necessary part of the wider data ecosystem.