Every three years, the ultimate race around the world takes place. The 2017-2018 Volvo Ocean Race has a starting line in Spain and a finish line in the Netherlands. At first glance, basic geography might suggest that there isn’t much distance covered between these two locations. However, the journey covers 45,000 miles by way of South Africa, Hong Kong, New Zealand, Brazil, and Sweden, to name just a few of the stops along the way.
The race isn’t for the faint of heart, quite literally. Each sailing team is comprised of 7 to 11 professional crew who don’t have much space to share on these 65-foot yachts. And sailing can be non-stop for three weeks at a time, often with grueling conditions that are unpredictable throughout the course of the 8 months of competition.
This is the backdrop that led one team to try something new. Team AkzoNobel decided to investigate how best to optimize conditions for their crew. Historically, variables such as weather and subsequent route decisions were the main focus in terms of looking for that competitive edge. But what if you could get insight into other conditional variables affecting the crew?
1. Finding answers to difficult questions through precise measurement
It turns out, you can. In fact, there are many more variables and subsequent outcomes that are the result of specific choices that need to be made right on the boat, often in real time. For example, how much sleep is just enough? How long is too long for a single shift? How often should a crewmember eat or rest? How many calories should they take in? How long should breaks be? And the list of questions with the answer “it depends” goes on and on.
Traditionally, most of these questions are answered by a mix of experience and predefined planning that can be adjusted on the fly (even if inexactly). And while experience and planning can serve a crew well, there is a certain amount of precision that’s missing. As the saying goes, you get what you measure. And by extension, the better your measurements, the more you’re likely to get.
2. Facilitating insight even under harsh conditions
But then, how might you facilitate precise measurements when you’re in the middle of nowhere? (That’s not just a saying, in this case: The race passes by Point Nemo, the spot on earth that is farthest from land.) This is where the concept of edge computing comes into play. As the Volvo Ocean Race so acutely illustrates, in the real world, a lot of useful data is generated at “the edge,” meaning not necessarily in the middle of a city with a strong Internet connection.
But now, especially with the prevalence of the Internet of Things (IoT) providing access to an unprecedented amount of data through sensor-enabled devices, it’s often assumed that the cloud is everywhere, with its distributed processing power available on demand to make insightful information out of all this raw data being collected. As that is only partially true; another solution is needed. Enter stage left: edge computing.
If you have the right local processing power, you can still gather and analysis quite a bit of data, all while being disconnected from the cloud. Then, when you’re within range of the cloud, you can sync up your data and analysis for a much more robust set of recommendations for the next leg of your trip.
3. Bringing together the power of the cloud and the edge
Case in point: Team AkzoNobel now has each of their crew members wear biometric sensors (embedded in wristwatches). This IoT data is then captured by a smartphone that acts as a gateway for a local WiFi network within the boat. The smartphone gateway then streams the biometric sensor data to a tiny onboard Raspberry Pi computer, enclosed in a watertight box and connected with USB power, that acts as the local processing power.
The Raspberry Pi has been configured with intelligent edge computing software which handles secure local data storage, synchronizing architecture, analytics models, and algorithms for data gathering and processing to provide real-time insights even from the middle of nowhere. This includes derived insights on each crew member’s fitness, performance, quality of sleep, stress levels, degree of exhaustion, reaction to weather conditions, and more.
The insights are displayed in real time through a custom web application the team can access while at sea. The data for each leg of the race is then synced with the cloud each time the yacht returns to shore and combined with larger historical data sets for predictive analysis for the next leg of the journey.
4. Harvesting gains from deeper insights
This allows for the best of both worlds: insight available in real time based on current conditions, but also deeper analysis and insight after each leg of the journey. Often a larger data set is required to find even small trends lines. But insight into a “small” trend can have huge implications. Even a mere 1 percent gain is significant in the world of ocean racing.
The crew is constantly learning from these insights and can understand the consequences of their choices more precisely and preemptively. For example, a crew member with the best of intentions might push himself until he breaks, but if the data suggests that a break earlier is better for the long run, he can adjust accordingly.
This level of insight also allows for a more tailored approach to food planning and consumption that is specific to each crewmember and their needs. Excessive food weight or less effective types of food, even when adjusted slightly, can secure significant gains. In the end, finding those optimal tradeoffs with more precise intelligence is the goal.
If you think about it, optimizing outcomes while participating in a competition with unpredictable (and often harsh) variables is a fairly accurate description of what it can be like running a business in the digital economy. But with the right combination of hardware, software, and services, you can achieve smooth sailing even while at the edge.
Watch this video to see how SAP Edge Services, as part of SAP Leonardo, can help you gain domain-specific insights in a digital world.