Proof-of-Concept: Databike Zeta 001 (DBZ-001)
- DBZ-001 is our first PoC in the Bikestream project. This concept we wanted to prove with the DBZ-001 is that we can develop a databike for real-time streaming of geolocation and internal electrical component information where the cyclist (or operator) has control over how and when their mobility data (aka consumer mobility data) is shared with unknown third parties, and creating the potential for a financial incentive through data sharing with unknown parties.
- The primary use-case the PoC addressed is the development of a financial incentive for cyclists to 1) convert their bikes into e-bikes, and 2) share their data with unknown third parties.
- DBZ-001 presents a general model for converting a traditional bicycle to a databike. Additionally, the development of a data stream and data marketplace on Streamr, a data sharing service on the Ethereum blockchain.
- The DBZ-001 has two on-frame single-board computers (SBCs), a Raspberry Pi 3 B+ and a Cycle Analyst 3 (CA3).
- The DBZ-001 collects geolocation (from a connection to a smartphone via bluetooth; info sent as NMEA strings) and internal electrical information (from the CA3) (“zeta-info”)
- The zeta-info is stored and processed on the RPi 3+ via a Python program into a JSON format and is outputted to Streamr’s command line interface (CLI) that connects the Python program to the publishing feature of Streamr and connects the JSON-formatted zeta-info to the data stream created on Streamr, which can be accessed in the Streamr data marketplace
- To make the data publicly available, we used Streamr Core, Streamr Marketplace and Streamr CLI. We used Streamr Core to create a data stream for the zeta-info, the Streamr marketplace to create a data product (comprised of multiple data streams of zeta-info that can be obtained from our DBZ-001 and from anyone who chooses to join the Cyclist Association product by adding their data stream) that is publicly accessible, and the Streamr CLI to connect the Python program to the data stream on Streamr so that we could run the RPi 3+ in headless mode (without a keyboard or display) and achieve real time data streaming.