Tag Archives: Amazon

Drone Commerce, Part 1: Same-day Delivery

As an aerospace engineer-turned-Internet software architect, it was probably only a matter of time before I wrote a post about the expanding use of Unmanned Aerial Vehicles (a.k.a. Drones). Now that we have two eCommerce giants entering the Drone Space makes it a good time as any to explore the practical viability of this from the point of view of someone who has built vehicles that fly, software that controls them, and large-scale eCommerce and data platforms.

In one corner we have Amazon’s exploration of drones for same-day delivery (interesting aside: Jeff Bezos, as owner of Blue Origin is also a commercial space entrepreneur). In the other corner with have Google’s recent purchase of Titan Aerospace for drone-based Internet service provision and Google Earth data capture (interesting aside: Google the ‘K’ in KML stands for Keyhole, something Google got when they bought Keyhole, Inc.—a company with a very interesting provenance to anyone who has worked in satellite technology for the IC).

Are these explorations of drone tech whacky uses of capital buy companies with more cash then they know what to do with or are they viable commercial pursuits with long, complex lead times? In part 1 of this series, I will look at the Amazon’s consideration of drones for same-day delivery. In part 2, I will look at Google’s ideas for Internet service provision and Google Earth data capture.

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To use drones (on a repeated basis) for package delivery, you have to overcome many, many challenges, including very big aerospace-related ones:

  • Large payload without large size
  • Safe, efficient flying (and delivery) operation
  • FAA approval to fly in populated places

This leaves out other non-aerospace challenges, ones Amazon has solved very well, such as efficient logistics management, protecting drones against hackers, notifying customers of immediate delivery, and other classic delivery challenges.

Challenge 1: Large Payload without Large Size

To be profitable (from a gross margin perspective), you need to either be able to deliver a good amount of packages (think how many packages a UPS or FedEx truck carries). This requires payload capacity. However, to fly drones to where people live and work, you need small drones. It is not viable to fly (and land) a MQ-9 Reaper-sized drone a 20-meter wingspan on residential street or commercial rooftop. You will most likely need a drone with a 1-2 meter wingspan (or body-span for quadcopter drones). Unfortunately small drones do not have high carrying capacity:

Body Span or Wing Span Payload
1 m 1 – 10 kg
3 m 5 – 20 kg
5 m 20 kg – 100 kg
10 m 100 kg – 400 kg

Payload Capacity by Wingspan with Current Drone Technology

The cause of is simply the laws of physics (specifically flight kinematics). The more you carry, the heavier you are. The heavier you are, the larger your wingspan or propellers need to be to generate sufficient lift. The large heavier you are, and the larger your wingspan—the more fuel (or heavier batteries) you need—compounding the problem. This is a non-trivial problem to solve. It is the major reason we do not have the capability for more than sub-orbital commercial space flight or commercially viable hovercrafts people can ride in residential areas—even 45 years after the Moon landing. It is also a problem that exacerbated by the style of flying needed for repeated delivery of packages throughout the day.

Challenge 2: Safe, Efficient Flying Operation

To be a viable vehicle for delivery, drones have to safely take off, navigate through a complex three-dimensional space, and land—repeatedly throughout the day, day-in and day-out. As this is a big set of challenges, it is easier to look at each individually.

Takeoff and Landing: Takeoff and landing is a lot more challenging than simple level flight. First, take consumes a lot more than level flight—the energy penalty depends on you payload, wingspan and runway size, exacerbating the “payload vs. size” challenge discussed above. Second, when you are flying slowly at low altitudes (i.e., just as you are taking off or landing) you are much higher risk of crashing due to wind shear-induced lost of lift: when this happens at 36,000’ you get turbulence; when this happens at 36’ you count on the training and experience of your pilot to adjust rapidly to keep you from hitting the ground. Unfortunately, drones do not have pilots. As such, the round-trip communication to a remote operator is not fast enough for instant adjustments, drones typically rely on onboard software to make immediate corrections. However, this software is not handling the simple operation of landing a drone on a remote landing strip, it is managing landing in a city (perhaps on a building or perhaps in your driveway). This obstacle can be overcome with better software (and lots of machine learning). Nevertheless you still have the “energy penalty” of taking off and landing over and over again through the day.

Cruising Navigation: Drones that delivery goods are going to have navigate a complex three-dimensional space populated with buildings, power wires, antennae, birds, other drones, and weather (small size and repeated take off and landing are going to require them to fly well-below 12,000’, making them subject rain, hail, snow, lower visibility and much more turbulent airflow than one encounters at altitudes that planes need to reach before pilots let you get up and move around the cabin). After 20 years of military use, we have gotten pretty good at letting drones to this successfully. Unfortunately you are flying at an altitude that is very inefficient. As a result you still have the nagging “energy penalty” cited several times already.

Challenge 3: Getting FAA Approval

This is the one challenge on my list that is based on socio-political systems—rather than flight dynamics and physics. However, it is an especially big barrier to overcome, as Amazon would not be getting approval large-scale, complex drone operation: many drones taking off and landing, many times a day, in populated area instead of drone that cruise at high altitudes or are operate at low scale by hobbyists at parks.

The numbers that drive the scale for profitable operations make this challenge especially difficult. Today, the piloted planes have 9.4 accidents per million flights (statistically very safe). Let’s use this to run some numbers:

  • If drones are as safe as planes and I have only five drones operating in each of the 50 largest cities and they are only doing 10 deliveries each a day (not very efficient vs. UPS), I will see a drone crash every 40 days
  • If drones are a bit less safe (likely as they fly at low altitude, take and land very often in complex environment, and do not the support of air traffic controllers and highly-trained pilots on board), I will see a crash every month.
  • These are not “landed hard and broken the container” crashes. They are “collided with building, power wire, tree or other obstacle”-type and “got flipped over in the crosswind and “dropped several stories into a street or rooftop”-type crashes.

What would this look like in the aviation regulatory space? The first crash would lead to a fleet grounding, NTSB investigation, and perhaps some hearings. A second crash after the first set of issues are addressed would lead to an even longer grounding and likely a change in allowed places of drone operation—especially if a person was hurt. At best, this would make commercial operation low margin; at worst, a big drag on the company’s reputation, stock price and liability.

Conclusion

A hate to be a naysayer—especially as a person who went to school to build planes, rockets and satellites that would give us the ability to travel more places, faster and more conveniently. However, it is hard to be profitable while fighting the laws of physics in complex conditions. Aviation technology can be improved, but generally not at the same rate as Moore’s Law (precisely because you are dealing with objects with much more mass than electrons and photons). As such, I do not see drone-based delivery being profitable—especially given the low-cost and high-efficiency of ground-based delivery (something that is going to get even better as the Internet of Things makes fleet management more efficient and Amazon’s machine learning lets them pre-position items before you even order them).

Jeff Bezos is a very, very smart man. It is my guess that his work in drone technology is not really focused on a better goods delivery mousetrap but instead something else that can scale at lower cost and higher efficiency. If I had to guess, I would say it would be related to streaming content or using peer-to-peer networking to bypassing carrier restrictions. That’s more of a topic or my next post in this series.

Updates:

Cloud Computing: Its not just about access from anywhere

Article first published as Cloud Computing: It’s Not Just About Access From Anywhere on Technorati.

Too many extolling the virtues of cloud computing are ignoring its most transformational benefits

Cloud computing has definitely moved into the mainstream. You now see commercials from Microsoft, Cisco, IBM and others every evening on prime time Cable TV. CNBC has created a Cloud Computing Special Report for investors to learn more about it. Even government agencies are now moving to cloud-based solutions.

Unfortunately, one of the most touted reasons we see for using cloud computing – that it provides universal access to data and applications from the Internet – has nothing to do with what cloud computing actually is. This is simply what web-based applications have been doing since the 1990s. True cloud computing offers a whole lot more.

In October 2009, The National Institute of Standards and Technology (NIST) published an excellent definition of cloud computing that calls out five essential characteristics that separate clouds from simple remotely hosted, web-based computing models:

  1. On-demand self-service
  2. Broad network access
  3. Resource pooling
  4. Rapid elasticity
  5. Measured service

I know, some of these terms are mouthful – especially to those who do “live and breathe” technology. However, they remove so much of the work and complexity that has so frequently made management of computing so painful and costly:

On-demand Self-Service (Think “Now”): With on on-demand self-service, you do not need to ask your provider to execute an “IT project” to enable you to use your application (or update it) to support a new business development. You can do whatever you need, when you need it – without the cost and delay of overhead managing your vendor.

Broad Network Access (Think “Convenience”): This lets you work wherever you need, whenever you need – from your work or home computer, netbook, tablet, or smartphone. Traditionally, this was done through browser, to bypass the need to install local software. However, the rise of (cloud-based) App Stores now allows us to install richer applications to access our data – wherever we are, on-demand.

These first two characteristics are what most people think of when talking about cloud computing. However, it is the next three characteristics that make true clouds stand out:

Resource Pooling (Think “Black Box”): Somewhere far away IT people are managing shared, redundant infrastructure across many data centers. They manage maintenance, business continuity, elimination of failures and bottlenecks, etc. You gain all of the benefit of these large-scale investments in time and resources – but without the need to do any work.

Rapid Elasticity (Think “No Limits”): You never have to worry about capacity planning. If you suddenly get a surge in traffic (due to an emergency or unexpected popularity) the computing resources you need are automatically – and immediately – available. You avoid slow-downs, timeouts and outages that waste time, cause frustration and turn away customers.

Measured Service (Think “Value”): Pay only for what you use – and no more. Rather than paying 100% for servers that you only use at 20% utilization, you pay for the exact number of resources you use, when you use them. The ideal cloud providers charge usage in terms that everyday people – not just IT systems administrators – understand and value.

cloudcomputing-180pxsWhen explaining these cloud computing characteristics to those whose “day jobs” are not in tech, I like to use the electricity analogy. When you buy a new television, you do not call the power company and ask them to initiate a project to set up your television. You simply plug it in and begin using it. If you don’t like where it is in your house, you unplug it, move it to a different room, and plug it in again. At the end of the month, you don’t pay for the power company’s generator and labor investments; you pay for the extra kilowatt-hours your television used.

Services that meet all five of these characteristics are so much more convenient and valuable than legacy computing models. That’s why cloud computing has the potential to be so transformational.