Q1. Korean Air’s R&D Center is now using Wingbits’ blockchain-verified ADS-B feed to support its ACROSS program. Concretely, how is your data being ingested and used in ACROSS development and testing, and what problem(s) does it solve that legacy feeds don’t?
Wingbits provides a data feed to the Korean Air R&D Department that contains aggregated telemetry data. This allows them to monitor and analyze the current airspace across multiple parameters for their research in the area of AAM. We cannot speak to how legacy networks ingest and process the data, but to our knowledge, we are the only network whose data has proof of location and proof of source.
Q2. Wingbits positions itself as a DePIN for aviation surveillance. What specific attributes of the DePIN model (token incentives, decentralization, edge receivers, on-chain proofs) make it especially well-suited for safety-critical aviation use cases like AAM?
For many years and until today, the collection and aggregation of data have mostly relied on individual volunteers setting up their own stations. The data that the station collects is sent to the network to perform some processing, which is then made available for purchase in various forms either as a data stream or fed into an application. The volunteers are given access to a subscription program that the network offers, which serves as the reward for the data they collect from their stations, which are sold to the networks. There is value in this business model given the profitability that most of these commercial networks exhibit.
Wingbits values the community of station hosts for their cooperation, time and effort in sending the data. They deserve to be rewarded with items that are much more valuable than a subscription. This has created an incentive model that produces much more efficient data density per station than other networks. For example, we have observed that throughout multiple peak times, Wingbits is tracking anywhere from 70 to 80% of the aircraft that other networks, whose advertised active stations are 10 to 12 times greater.
Q3. When airline R&D teams and air navigation service providers need “aviation-grade” reliability and auditability, how do you demonstrate that your blockchain verification and encryption meet those standards? Any certifications, SLA metrics, or audit processes you can describe?
Regulators, such as the FAA, have performance requirements for ADS-B systems needed for air traffic management, though there are no specific certifications needed for ADS-B stations used in situational awareness and non-safety related use cases. At Wingbits, we therefore let the data demonstrate our quality.
We have added some significant improvements that our competitors are unable to provide: proof of source of data (we know, at a hardware level, the exact station the data is originating from) and proof of location (we know where the station is located).
Q4. Tokenized participation is core to your architecture. How do you design incentive mechanisms so contributor rewards don’t compromise data quality or create perverse incentives (e.g., false reports, duplicate claims)?
The tokenization aligns directly with our business goals. We created a performance model that rewards users who have a set-up that runs constantly, covering as much area as possible, as close as possible to major airports. We workshopped the rewards engine in such a way that it reduces the incentives to cheat. For example, it doesn’t matter if you send duplicates of the same data points because only unique data points will count towards your rewards.
We also run continuous data quality checks on the data itself, and if we ever identify a strange case, we can ban the station from the network. This creates a network that is able to reward people at scale while still keeping the latency low and the quality high.
Q5. ADS-B data is sensitive and can be abused if misused. What privacy, access-control and anti-spoofing measures are implemented at the receiver, network and blockchain layers to keep surveillance data secure and compliant with aviation/regulatory requirements?
This might sound counterintuitive, but the ADS-B data is not private. It is broadcast on public radio, and anyone can listen to it. We only collect it, and therefore, there are very few regulatory requirements that we need to follow.
The data can be used for multiple use cases, some more strict than others. On the network level, we have really high station GPS accuracy, and we only accept traffic from stations that were onboarded in-factory.
Q6. Wingbits recently expanded via a satellite launch and fundraising. How do satellite feeds and space-based receivers change the coverage, latency and redundancy picture compared with terrestrial crowd-sourced receivers for global AAM operations?
The satellite feed allows us to validate the data we’re collecting from the terrestrial network. Think of it as a constant check as the satellite covers the area it traverses.
Q7. Integration with legacy ATM, FAA/EASA/ICAO processes and local regulators is often the hardest part. How are you approaching regulatory acceptance and data-sharing agreements, and what roadblocks have you encountered so far with airline or government partners?
This will always be the case, especially for a heavily regulated industry. Fortunately, there are use cases that fall outside regulatory realms. We hope that by partnering with organizations that already have ties to the regulatory bodies, as well as research-oriented parties like Korean Air and universities, it will make navigating roadblocks less of a concern. Ultimately, we want to be the best at collecting and delivering data to the end users, not navigating the regulatory landscape.
Q8. Korean Air’s use represents a move from proof-of-concept to operational testing. What engineering and governance lessons did Wingbits learn from early pilots that you changed or hardened to meet airline R&D needs?
We learnt a lot from Korean Air’s testing of our data quality for fidelity and latency.
Q9. For cities and operators planning eVTOL corridors, what is the role of decentralized flight-intelligence providers like Wingbits versus centralized surveillance incumbents? Do you see these systems as complementary, and if so, how do you federate trust across them?
It will likely be the end users and those ingesting the data that will determine how best to utilize both systems. Those ingesting data should be able to ingest from both types of networks, merging, processing and performing their analysis. Both systems are complementary, serving as validation for each other.
Q10. As AAM traffic density grows (dense urban corridors), how does Wingbits plan to scale data ingestion, on-chain verification and query performance while keeping latency low for real-time routing decisions?
We have a very talented engineering team ensuring the backbone of the infrastructure is set up to scale the processes. They have done a wonderful job of scaling it from a few hundred stations to nearly 5,000 at the moment. We are confident that they are up to any challenges that may pop up in this area.
Q11. From a commercial standpoint, what business models are you exploring with enterprise partners (data subscriptions, licensing, tokenized marketplaces, revenue-share with contributors), and how do you balance commercialization with openness needed for safety and interoperability?
That’s the beauty of a startup that is being led by founders. In our early stages, we are not bound by trying to implement a SaaS model that caters to Wall Street’s desires. We are open to speaking to any party that has a relevant interest in partnering with us in any capacity: as a data subscriber, licensed distributor, or as a strategic or marketing partner.
Q12. Looking five years out, what are the most exciting global projects or partnerships you hope to enable with the Wingbits DePIN, and what would success look like for both the aviation industry and the contributor community?
Five years seem so far away, given what our team has accomplished in the past two. The beauty of data and aviation is that new use cases continue to emerge as more mainstream research and new types of aircraft occupy the airspace. We believe that Wingbits will be a trailblazer in the way the community is taken care of and incentivized. As the well-respected Charlie Munger stated, “Show me the incentive, and I will show you the outcome”. We think the rapid network growth exemplifies this. We aim to be the backbone of aviation positional data, powering applications but also proactively and creatively working with industry players to develop applications that can better serve their rapidly changing operational needs.
Related reading: Vitalik Buterin Warns On-Chain Privacy Risk Is ‘Extremely High’ – Are Blockchains Twitter for Your Bank Account?.
