oron

I just use a single k3s install on a single bare metal from Hetzner or OVH, works like charm, very clean deployments, much more stable than docker-compose and 1/10 of the cost of AWS or similar.

Thx for taking the time to write. We will look into it.

Those are all excellent questions and suggestions. I recommend discussing them with our customer support team.

We have a pricing page here https://skypath.io/start_a_trial/

Typically, flights do not deviate from their planned routes for non-severe turbulence levels. It's safer and simpler to have passengers remain seated with the seatbelt sign on. Our model considers weather inputs alongside real-time data, acknowledging that weather is continuously changing and somewhat unpredictable. Therefore, we don't perceive this issue as significant

Good question, turning on the seatbelt sign in this case is a good start.

What's the biz model ?

Yes, satellite internet is now standard on many Western airlines. In addition to this, we utilize weather data and real-time turbulence reports to predict Clear Air Turbulence (CAT) events across the entire sky, even where iPads are currently not on flights.

Thank you. We are actively working to onboard as many airlines as possible, and partnering with Delta would be highly beneficial. The more data we have, the safer and more efficient flights become.

Regarding the integration with Jeppesen, we would greatly appreciate hearing more about any issues you encounter and receiving your feedback

Our solution is compatible with Airbus, Boeing, or any other aircraft. It's important to note that connecting to the aircraft systems can be more expensive and add maintenance and complexity costs for the airline.

We have a partnership with Jeppesen, a Boeing company, for their Flight Deck Pro product. With this collaboration, users can access our data layer and predictions, and also report real-time turbulence within their app. While I'm not extensively familiar with the inner workings of ForeFlight, based on what I've heard, it relies on an external hardware solution, and its coverage and quality are not comparable

Five hours is a bit long; you can choose in the app how far ahead you would like to see. We typically recommend looking two hours ahead. This way, for the initial two hours, you'll have some data that may be partially outdated but still better than having no information at all.

More predictable routes and minimizing encounters with CAT can indeed help reduce fuel consumption while maintaining safety. This is a relatively small saving for each flight which can add up to a big chunk at the end of the year.

Some of the most severe injuries occur among crew members because they must rush to secure passengers in their seats, often being the last to fasten their own seat belts. Additionally, when turbulence reaches a certain intensity, the aircraft must undergo costly structural testing on the ground, which disrupts the airline's schedule significantly.

nice work! where is the data coming from?

It depends on the provider that the airline has partnered with, I suppose. We don't manage the satellite connectivity, so I can't provide specifics on that. However, in areas with fewer ground stations, disruptions are more likely. Our app and servers are designed to function effectively on unreliable internet connections. it downloads prediction data for several hours ahead and is capable of uploading turbulence data once the internet connection stabilizes.

Can run in the background, pilot can use any other app meanwhile. Or just leave the iPad with screen off. Our app keeps recording and alerting as long as you are in flight.

The second is closer to reality , initially let pilots (lots of them) label flight events and after landing take all data and build the algorithm around their initial labels. The when there are more pilots let them label agree / disagree and relabel etc.

Another aspect is you have usually two iPads in the cockpit for captain and first officer so you can correlate and match what both accelerometers read.

Cockpit WiFi that's open only for the crew.

Valid observation: turbulence patterns differ from pilot tapping and can be recognized and disregarded. While complete elimination of false positives isn't always feasible, employing various techniques allows us to significantly minimize such occurrences, thereby mitigating their impact.

By analyzing the acceleration patterns that the iPad the pilot has in the cockpit which is securely attached to the aircraft is measuring. Cleaning out noise such as engine and other non CAT noise and training our model to identify these and also predict future events in the next 3 hours by looking at the current data. It takes millions of events and lots of pilots which help train the initial model and fine tune it.

This solution is for commercial airlines, pilots and dispatchers and for general and business aviation.

Employee of SkyPath here. We are trying to give a solution to this problem dedicated thread here : https://news.ycombinator.com/item?id=40828180

Good comment! our algorithms take into account time of report as recorded by the aircraft so latency or offline aircraft is not an issue. Surprisingly most CAT phenomena is pretty stable and can stay in the same area for hours at time.

Nope, company was started by commercial / ex-military pilots who scratched their own itch and still today is run by pilots :-)

Right now flight predictions and route quality are offered only to pilots who are operating the flight and to dispatchers. There are discussions with the airlines to integrate our technology into their apps but at the moment there is no such solution available.

We had to give incentives for the first airline partners and give the product for free for a long trial period at the early years to be able to have initial installs. It was a long ride including Covid which came in the middle and didn't help. In the last years since we have several big airline partners this is less of a problem.

Apart from usual SW tests, Lots of testing with airlines and experienced pilots. Processing feedback and improving the model step by step over the course of several years.

At SkyPath we have a simple solution that doesn't involve installing any HW on the aircraft and uses the airline issued iPad the pilot already uses for other important tasks to help fight Clear Air Turbulence. We use the iPad's accelerometers to measure and report turbulence in real time and collect this data via the internet where it's processed in AWS by our machine learning model to produce customized alerts for each flight that uses our service on incoming CATs in their route.

Signed as in purchased a subscription for our service to provide data from their aircraft (using iPad sensors pilots are using) and get real time alerts and predictions regarding their flight and route.