Pebble Responsible Data Use Assessment Summary
LAST UPDATED: JULY 1, 2022
LAST UPDATED: JULY 1, 2022
This document is a summary of Sidewalk Labs’ Responsible Data Use Assessment for its Pebble product. (Sidewalk Labs is operated by Google LLC)
Sidewalk Labs conducts Responsible Data Use Assessments to ensure its work respects and protects individuals’ privacy, and that we are using data responsibly. Like a Privacy Impact Assessment, a Responsible Data Use Assessment identifies potential privacy risks at an early stage so that they can be appropriately mitigated. Additionally, Sidewalk Labs’ Responsible Data Use Assessments are designed to include broader considerations around data ethics to ensure the application of responsible data practices.
The Responsible Data Use Assessment only reflects Sidewalk Labs’ assessment of its Pebble product, and is not intended to make any representations on behalf of its customers or any other party.
Parking in cities is a complex management problem. But parking operators, real estate developers, and municipal agencies don’t have access to the information they need to manage their parking supply and curb spaces most effectively.
Pebble: a low-cost, easy-install, privacy-preserving vehicle sensor designed to help manage parking and the curb in innovative and sustainable ways. Pebble provides real-time data about parking space availability, with a dashboard to help analyze historical parking patterns. These insights can help communicate space availability to customers, reduce circling and vehicle emissions, and create shared parking zones that minimize the number of spaces built in the first place.
Pebble includes a set of curb or parking space occupancy sensors that are designed to be applied to the ground, with each occupancy sensor using magnetometers and infrared sensing to detect only whether there is a vehicle above it or not. Pebble also includes a gateway that enables communication with the occupancy sensors, and an API for customers to access Pebble data and functions.
Sidewalk Labs has a comprehensive set of data security measures to safeguard data and prevent unauthorized or inappropriate access to data, such as encryption of data at rest and in transit, and the use of Two-Factor Authentication. Additionally, Pebble has been designed to include additional mitigation measures to address potential privacy and data governance considerations, including:
Pebble Sensors and Gateways Apply Data Minimization and Do Not Collect Personal Information
Pebble sensors and gateways do not collect personal information. Pebble sensors are designed to sense only whether a vehicle is present in a parking or curb space, using a magnetometer and infrared sensing. They do not collect data on the specific characteristics of vehicles, license plates, the number of vehicle occupants, data about the vehicle occupants themselves, nor data about any other people. Only Pebble sensors are visible to Pebble gateways, and Pebble sensors and gateways are designed to only communicate with each other and the Pebble API.
Access to Pebble Data Is Restricted
Sidewalk Labs restricts access to Pebble data on a need-to-know basis. A Pebble customer’s users must be properly authenticated and authorized to access Pebble data.
Use of Pebble User Data Is Limited to User Login and Communication with Consent
Pebble only receives and uses personal information for the purposes of authenticating customers’ authorized users, communicating with them with their consent, ensuring the security of the Pebble, and delivering the services associated with Pebble.
Sidewalk Labs' Responsible Data Use Assessment is used to ensure its products and pilots respect and safeguard individuals’ privacy and use data responsibly by identifying potential risks at an early stage so that they can be appropriately mitigated. Pebble is a product that is designed to help parking and curb space managers plan and manage the occupancy of spaces by vehicles, and potential privacy and data governance considerations have been appropriately mitigated, in accordance with existing best practices.