Google Fit, developer's view

Aug 27, 2014Download as PPTX, PDF3 likes2,438 views

This document discusses Google Fit, an API that allows apps to access fitness and health data from sensors and integrate that data into the Google Fit platform. It outlines the key components of Google Fit including the data store, sensor framework, and data types. It also describes how sensor data flows from devices into the Google Fit storage and provides examples of standard and custom data types. Finally, it notes some areas for potential improvement in Google Fit.

Google Fit
App Developer View
Prepared for Personal Analytics Meetup
By Gene Leybzon, Aug 2014

Applications That Can benefit from
integration with Google Fit API
Health/Fitness
Data Collection
Wearable Sensor-based
apps
Health/Fitness
Behavior Analytics
Statistical/Personal
Analytics

What’s in Google Fit?
Google Fit APIs
Permissions/User Controls
Data Store
Sensor Framework

What’s defined in Android APIs?
Sensor APIs
(access to raw
sensor data)
Recording APIs
(Subscriptions for
data storage)
History APIs
(Bulk operations
on recorded data)

Data flow from sensor to Fitness
Store
Sensors
(Android or
BTLE-connected)
Sensor
Adapters
Fitness
Recording
API

Defined by Google
Custom
Custom
Data Types

Examples of Data Types Defined by
Google
Name Description
com.google.height User’s height [m]
com.google.speed User’s speed [m/s]
com.google.heart_rate.bpm Heart rate [beats per min]
com.google.heart_rate.summary Max/Min/Average Heart rate [beats
per min]

Creating Custom Data Types
Create data type
request using
data type builder
Invoke request
using history API
Check Result
(asynchronously)

Working with fitness history
Read historical data
Insert data set
Delete data

Access to the row sensor data
List data sources
Register a new listener
Unregister listener
Scan available BT devices
Claim BT device
Release BT device

What is missing?
 Structured data support for more data types
 Local storage (on device)
 More advanced data aggregation, statistical features
 Support for other eco-systems (iOS)

This document provides an overview of the Google Fit platform and APIs for accessing fitness data on Android. It describes the basic representations for sensors, data types, data points and sessions. It also outlines the permissions and scopes required to access fitness data. The key APIs covered are the Sensors API for reading raw sensor data, the Recording API for storing fitness data, the History API for accessing stored data, and the Sessions API for creating and managing fitness sessions. Instructions are provided on setting up projects, connecting to the Fitness service, recording and reading data, and using the APIs to work with sensors, history and sessions.

Samsung S Health Service SDKGene Leybzon

��

This document discusses Samsung's S Health SDKs for wearable devices. It outlines popular health and fitness SDKs including Apple HealthKit, Google Fit, and Samsung S Health. It describes the components of Samsung S Health including APIs for mobile devices, a health server for storing records, and a web SDK. It also details the features and architecture of Samsung S Health as well as the process for developing apps using the SDK.

Introduction to Google FitQuantified Self Dublin

��

Google Fit is an open ecosystem that allows fitness data from different devices and apps to be stored in a central repository accessible from multiple devices. Developers can integrate with Google Fit using a REST API or Android SDK to upload fitness data from any wearable or sensor to the central repository, and access data created by other apps. This allows users' fitness data to persist even if they upgrade their fitness devices.

Building a Custom Polling Importer in AEMMarcel Boucher

��

This document discusses developing a custom polling importer to ingest external content into AEM. It describes adding a new importer scheme for a Jira feed, implementing an OSGi bundle to define the importer as a service, and processing the Jira XML results by applying calculations and removing unnecessary elements using an XSLT stylesheet. The full implementation allows polling a Jira instance on a scheduled basis and importing the results into AEM.

Introduction To Google FitAllen Thomas Varghese

��

Google Fit is an open ecosystem that allows fitness data from different devices and apps to be stored in a central repository accessible from multiple devices. Developers can integrate with Google Fit using a REST API or Android SDK to upload fitness data from any wearable or sensor to the central repository, and to access data created by other apps. Users' fitness data will persist even if they upgrade their fitness devices.

Insight Data Science Final Presentation for Active Me - Lois SmithLois K. Smith

��

Apple Health Kit from the Application Developer Point of ViewGene Leybzon

��

HealthKit is Apple's health and fitness data platform that allows apps to access and store users' health and fitness data. It includes APIs for collecting sensor data, accessing health records, and performing analytics on aggregated user data. Developers can use HealthKit to access data from various sources and apps, perform queries, and sync data to cloud storage, while requiring users' permission for each type of data access. The platform continues to expand its capabilities but still lacks some features like support for additional data types and integration with other platforms and standards.

Fitbit-Final PresentationAvik Das

��

The document discusses several projects related to analyzing data from Fitbit activity monitors. It covers developing APIs to access Fitbit data using OAuth protocols and ensuring data accuracy. It also discusses using Fitbit data for predictive analytics to detect potential depression and comparing Fitbit and treadmill step count data. Machine learning algorithms like SVM and Bayes classification are used for the predictive analytics. Linear regression is used to analyze the relationship between Fitbit and treadmill step counts. The projects aim to better utilize Fitbit data through APIs, analytics and comparing against other activity monitors.

Big DataMarian Borca

��

Fitbit retail packagekrettle

��

Fitbit is a wearable device and online platform that allows users to track their daily activity, exercise, and sleep. The small device can be worn on the wrist or hip and automatically monitors steps, distance, calories burned, and sleep quality. All data collected by the Fitbit is wirelessly synced to the Fitbit website where users can view detailed stats, compete with friends and family, and gain insights from motivational tools and analytics to help improve their lifestyles.

Scrape Uber Eats API for Enhanced Restaurant Insights.pptxReal Data API

��

Scrape Uber Eats API for Enhanced Restaurant Insights.pdfReal Data API

��

Internet of Things Chicago - MeetupJason Lobel

��

The document discusses capturing and analyzing high-velocity, high-volume machine data from internet-connected devices and sensors. It describes considerations for capturing streaming data, such as using NoSQL databases and cloud hosting. APIs can be used to access both historical and real-time data and fuel interactive visualizations and smart applications. Machine learning algorithms applied to the data through APIs can power recommendations, predictions, fraud detection and more for applications in retail and e-commerce.

Contextually Relevant Retail APIs for Dynamic Insights & ExperiencesJason Lobel

��

1. SwiftIQ provides contextual retail APIs that power omni-channel personalization, smarter analytics, and category management for retailers. 2. The APIs allow retailers to activate insights and digital experiences across channels by enabling data from different sources to be machine readable and accessible via queries. 3. SwiftIQ's platform includes data APIs, query APIs, algorithm APIs, and applications that use predictive algorithms and machine learning to extract insights from retail data.

Skill up in machine learning using Azure MLMostafa

��

Data Scraping Insights with Zomato, Swiggy, and Zepto APIs.pdfReal Data API

��

Data Scraping Insights with Zomato, Swiggy, and Zepto APIs.pptxReal Data API

��

Integrating GoogleFit into Android AppsGiles Payne

��

Giles Payne presented on integrating GoogleFit into Android apps. He discussed getting an API key from the Google API console, adding the Fitness API dependency to build.gradle, creating a GoogleApiClient and enabling auto-manage, subscribing to data sources like step count, and querying the data source to retrieve aggregated fitness data in buckets by time range. Common issues include not needing to specify an API key and needing to reconnect after 48 hours to continue querying data.

CCNSP - Google AnalyticsAlan K'necht

��

This document summarizes a presentation about frequently overlooked features in Google Analytics. It discusses why web analytics is a team effort and provides an overview of data segmentation and in-page analytics tools. The bulk of the presentation focuses on configuring goals and funnels in Google Analytics to track key metrics like registrations and engagement. It also covers creating custom reports to organize data as needed. Q&A and training sections are dedicated to these topics. The document concludes with recommendations on tracking downloads and RSS subscribers.

Extract Swiggy Instamart API for Grocery Data Collection.pdfReal Data API

��

Scraping the Swiggy Instamart API allows businesses to access valuable data from Swiggy's quick-commerce grocery platform. By extracting real-time information on product availability, pricing, discounts, and customer reviews, companies can gain insights into consumer behavior, market trends, and competitive pricing. This data can also be used to monitor inventory, analyze regional preferences, and optimize product listings. Additionally, scraping helps in keeping up with dynamic price changes, enabling businesses to make data-driven decisions to improve their offerings and customer experience.

Extract Swiggy Instamart API for Grocery Data Collection.pptxReal Data API

��

Learn how to scrape Swiggy Instamart API to collect valuable grocery data. Optimize your data collection with our comprehensive guide. Scraping Swiggy Instamart API data, businesses can access real-time information on grocery products, prices, and availability. This data helps in understanding market trends, identifying popular products, and analyzing competitive pricing. Extracting Swiggy Instamart API data allows for a detailed view of market dynamics and consumer preferences.

AnDevCon - Tracking User Behavior CreativelyKiana Tennyson

��

This document discusses tracking user behavior within mobile applications using Google Analytics. It provides an overview of analytics and user tracking, and describes how Google Analytics can be implemented on Android applications. Key details include how Google Analytics collects and stores data on the device before transmitting it to Google's servers, and how common interaction types like pageviews, events, and ecommerce can be tracked. The document also discusses reporting features in Google Analytics like the Core Reporting API and different dimensions and metrics that can be queried.

Press Association Football API Services presentationPressAssociation

��

The document discusses potential uses of football data delivered via an API platform, including powering websites and apps live and automatically, visualizing statistics in widgets for multiple platforms, and providing data-driven solutions for broadcast and pundit tools. It provides examples of how live match data and statistics could be used to create dynamic and engaging experiences for users across websites and other digital platforms.

Google Firebase - Analytics, Remote Config, AuthenticationBirender Singh

��

Google cloud platformrajdeep

��

- The document discusses Google's Prediction API which allows users to build machine learning models and make predictions by uploading training data, training models on that data, and then making predictions on new data. - It provides an example of using the Prediction API to automatically categorize and respond to customer emails by language by training on tagged emails and predicting the language of new emails. - The process involves uploading training data, training a model on that data, and then making predictions on new data using the trained model to receive a predicted language label.

Li charles emerging biometrics identity services in the cloud 02122015b - ...Charles Li

��

Biometrics identity services in the cloud are emerging as one of the major trends in the future of biometrics applications. The driving forces are biometrics data collection proliferation, demand for mobility, standard adoption, biometrics commoditization and advancement of cloud technologies. We will propose a cloud-based biometrics identity services reference architecture and identify emerging technologies and standards to enable its deployment. Highlights: • Identifying the trends in biometrics applications, including • Envisioning the emerging efforts relevant to cloud-based data proliferation, mobility, commoditization and etc. biometrics identity services, including standard • Leverage a cloud-based reference architecture for development, paradigm shift to define requirements, etc. biometrics identity services

Both Feet on the Ground - Generative Artificial IntelligencePete Nieminen

��

Endpoint Backup: 3 Reasons MSPs Ignore ItMSP360

��

More Related Content

Similar to Google Fit, developer's view (20)

Apple Health Kit from the Application Developer Point of ViewGene Leybzon

��

Fitbit-Final PresentationAvik Das

��

Big DataMarian Borca

��

Fitbit retail packagekrettle

��

Scrape Uber Eats API for Enhanced Restaurant Insights.pptxReal Data API

��

Scrape Uber Eats API for Enhanced Restaurant Insights.pdfReal Data API

��

Internet of Things Chicago - MeetupJason Lobel

��

Contextually Relevant Retail APIs for Dynamic Insights & ExperiencesJason Lobel

��

Skill up in machine learning using Azure MLMostafa

��

Data Scraping Insights with Zomato, Swiggy, and Zepto APIs.pdfReal Data API

��

Data Scraping Insights with Zomato, Swiggy, and Zepto APIs.pptxReal Data API

��

Integrating GoogleFit into Android AppsGiles Payne

��

CCNSP - Google AnalyticsAlan K'necht

��

Extract Swiggy Instamart API for Grocery Data Collection.pdfReal Data API

��

Extract Swiggy Instamart API for Grocery Data Collection.pptxReal Data API

��

AnDevCon - Tracking User Behavior CreativelyKiana Tennyson

��

Press Association Football API Services presentationPressAssociation

��

Google Firebase - Analytics, Remote Config, AuthenticationBirender Singh

��

Google cloud platformrajdeep

��

Li charles emerging biometrics identity services in the cloud 02122015b - ...Charles Li

��

Apple Health Kit from the Application Developer Point of ViewGene Leybzon

��

Fitbit-Final PresentationAvik Das

��

Big DataMarian Borca

��

Fitbit retail packagekrettle

��

Scrape Uber Eats API for Enhanced Restaurant Insights.pptxReal Data API

��

Scrape Uber Eats API for Enhanced Restaurant Insights.pdfReal Data API

��

Internet of Things Chicago - MeetupJason Lobel

��

Contextually Relevant Retail APIs for Dynamic Insights & ExperiencesJason Lobel

��

Skill up in machine learning using Azure MLMostafa

��

Data Scraping Insights with Zomato, Swiggy, and Zepto APIs.pdfReal Data API

��

Data Scraping Insights with Zomato, Swiggy, and Zepto APIs.pptxReal Data API

��

Integrating GoogleFit into Android AppsGiles Payne

��

CCNSP - Google AnalyticsAlan K'necht

��

Extract Swiggy Instamart API for Grocery Data Collection.pdfReal Data API

��

Extract Swiggy Instamart API for Grocery Data Collection.pptxReal Data API

��

AnDevCon - Tracking User Behavior CreativelyKiana Tennyson

��

Press Association Football API Services presentationPressAssociation

��

Google Firebase - Analytics, Remote Config, AuthenticationBirender Singh

��

Google cloud platformrajdeep

��

Li charles emerging biometrics identity services in the cloud 02122015b - ...Charles Li

��

Recently uploaded (20)

Both Feet on the Ground - Generative Artificial IntelligencePete Nieminen

��

Endpoint Backup: 3 Reasons MSPs Ignore ItMSP360

��

UiPath Automation Developer Associate Training Series 2025 - Session 1DianaGray10

��

Welcome to UiPath Automation Developer Associate Training Series 2025 - Session 1. In this session, we will cover the following topics: Introduction to RPA & UiPath Studio Overview of RPA and its applications Introduction to UiPath Studio Variables & Data Types Control Flows You are requested to finish the following self-paced training for this session: Variables, Constants and Arguments in Studio 2 modules - 1h 30m - https://academy.uipath.com/courses/variables-constants-and-arguments-in-studio Control Flow in Studio 2 modules - 2h 15m - https:/academy.uipath.com/courses/control-flow-in-studio ⁉️ For any questions you may have, please use the dedicated Forum thread. You can tag the hosts and mentors directly and they will reply as soon as possible.

UiPath Agentic Automation Capabilities and OpportunitiesDianaGray10

��

Learn what UiPath Agentic Automation capabilities are and how you can empower your agents with dynamic decision making. In this session we will cover these topics: What do we mean by Agents Components of Agents Agentic Automation capabilities What Agentic automation delivers and AI Tools Identifying Agent opportunities ❓ If you have any questions or feedback, please refer to the "Women in Automation 2025" dedicated Forum thread. You can find there extra details and updates.

Unlocking DevOps Secuirty :Vault & KeylockHusseinMalikMammadli

��

DevOps iş təhlükəsizliyi sizi maraqlandırır? İstər developer, istər təhlükəsizlik mühəndisi, istərsə də DevOps həvəskarı olun, bu tədbir şəbəkələşmək, biliklərinizi bölüşmək və DevSecOps sahəsində ən son təcrübələri öyrənmək üçün mükəmməl fürsətdir! Bu workshopda DevOps infrastrukturlarının təhlükəsizliyini necə artırmaq barədə danışacayıq. DevOps sistemləri qurularkən avtomatlaşdırılmış, yüksək əlçatan və etibarlı olması ilə yanaşı, həm də təhlükəsizlik məsələləri nəzərə alınmalıdır. Bu səbəbdən, DevOps komandolarının təhlükəsizliyə yönəlmiş praktikalara riayət etməsi vacibdir.

Build with AI on Google Cloud Session #4Margaret Maynard-Reid

��

Understanding Traditional AI with Custom Vision & MuleSoft.pptxshyamraj55

��

Understanding Traditional AI with Custom Vision & MuleSoft.pptx | ### �ݺ�ߣ Deck Description: This presentation features Atul, a Senior Solution Architect at NTT DATA, sharing his journey into traditional AI using Azure's Custom Vision tool. He discusses how AI mimics human thinking and reasoning, differentiates between predictive and generative AI, and demonstrates a real-world use case. The session covers the step-by-step process of creating and training an AI model for image classification and object detection—specifically, an ad display that adapts based on the viewer's gender. Atulavan highlights the ease of implementation without deep software or programming expertise. The presentation concludes with a Q&A session addressing technical and privacy concerns.

TrustArc Webinar - Building your DPIA/PIA Program: Best Practices & TipsTrustArc

��

Understanding DPIA/PIAs and how to implement them can be the key to embedding privacy in the heart of your organization as well as achieving compliance with multiple data protection / privacy laws, such as GDPR and CCPA. Indeed, the GDPR mandates Privacy by Design and requires documented Data Protection Impact Assessments (DPIAs) for high risk processing and the EU AI Act requires an assessment of fundamental rights. How can you build this into a sustainable program across your business? What are the similarities and differences between PIAs and DPIAs? What are the best practices for integrating PIAs/DPIAs into your data privacy processes? Whether you're refining your compliance framework or looking to enhance your PIA/DPIA execution, this session will provide actionable insights and strategies to ensure your organization meets the highest standards of data protection. Join our panel of privacy experts as we explore: - DPIA & PIA best practices - Key regulatory requirements for conducting PIAs and DPIAs - How to identify and mitigate data privacy risks through comprehensive assessments - Strategies for ensuring documentation and compliance are robust and defensible - Real-world case studies that highlight common pitfalls and practical solutions

DealBook of Ukraine: 2025 edition | AVentures CapitalYevgen Sysoyev

��

Transform Your Future with Front-End Development TrainingVtechlabs

��

Kickstart your career in web development with our front-end web development course in Vadodara. Learn HTML, CSS, JavaScript, React, and more through hands-on projects and expert mentorship. Our front-end development course with placement includes real-world training, mock interviews, and job assistance to help you secure top roles like Front-End Developer, UI/UX Developer, and Web Designer. Join VtechLabs today and build a successful career in the booming IT industry!

The Future of Repair: Transparent and Incremental by Botond DénesScyllaDB

��

Regularly run repairs are essential to keep clusters healthy, yet having a good repair schedule is more challenging than it should be. Repairs often take a long time, preventing running them often. This has an impact on data consistency and also limits the usefulness of the new repair based tombstone garbage collection. We want to address these challenges by making repairs incremental and allowing for automatic repair scheduling, without relying on external tools.

UiPath Automation Developer Associate Training Series 2025 - Session 2DianaGray10

��

In session 2, we will introduce you to Data manipulation in UiPath Studio. Topics covered: Data Manipulation What is Data Manipulation Strings Lists Dictionaries RegEx Builder Date and Time Required Self-Paced Learning for this session: Data Manipulation with Strings in UiPath Studio (v2022.10) 2 modules - 1h 30m - https://academy.uipath.com/courses/data-manipulation-with-strings-in-studio Data Manipulation with Lists and Dictionaries in UiPath Studio (v2022.10) 2 modules - 1h - https:/academy.uipath.com/courses/data-manipulation-with-lists-and-dictionaries-in-studio Data Manipulation with Data Tables in UiPath Studio (v2022.10) 2 modules - 1h 30m - https:/academy.uipath.com/courses/data-manipulation-with-data-tables-in-studio ⁉️ For any questions you may have, please use the dedicated Forum thread. You can tag the hosts and mentors directly and they will reply as soon as possible.

AIXMOOC 2.3 - Modelli di reti neurali con esperimenti di addestramentoAlessandro Bogliolo

��

Stronger Together: Combining Data Quality and Governance for Confident AI & A...Precisely

��

Unlock AI Creativity: Image Generation with DALL·EExpeed Software

��

Discover the power of AI image generation with DALL·E, an advanced AI model that transforms text prompts into stunning, high-quality visuals. This presentation explores how artificial intelligence is revolutionizing digital creativity, from graphic design to content creation and marketing. Learn about the technology behind DALL·E, its real-world applications, and how businesses can leverage AI-generated art for innovation. Whether you're a designer, developer, or marketer, this guide will help you unlock new creative possibilities with AI-driven image synthesis.

Cloud of everything Tech of the 21 century in AviationAssem mousa

��

FinTech - US Annual Funding Report - 2024.pptxTracxn

��

UiPath Document Understanding - Generative AI and Active learning capabilitiesDianaGray10

��

This session focus on Generative AI features and Active learning modern experience with Document understanding. Topics Covered: Overview of Document Understanding How Generative Annotation works? What is Generative Classification? How to use Generative Extraction activities? What is Generative Validation? How Active learning modern experience accelerate model training? Q/A ❓ If you have any questions or feedback, please refer to the "Women in Automation 2025" dedicated Forum thread. You can find there extra details and updates.

Gojek Clone Multi-Service Super App.pptxV3cube

��

World Information Architecture Day 2025 - UX at a CrossroadsJoshua Randall

��

User Experience stands at a crossroads: will we live up to our potential to design a better world? or will we be co-opted by “product management” or another business buzzword? Looking backwards, this talk will show how UX has repeatedly failed to create a better world, drawing on industry data from Nielsen Norman Group, Baymard, MeasuringU, WebAIM, and others. Looking forwards, this talk will argue that UX must resist hype, say no more often and collaborate less often (you read that right), and become a true profession — in order to be able to design a better world.

Both Feet on the Ground - Generative Artificial IntelligencePete Nieminen

��

Endpoint Backup: 3 Reasons MSPs Ignore ItMSP360

��

UiPath Automation Developer Associate Training Series 2025 - Session 1DianaGray10

��

UiPath Agentic Automation Capabilities and OpportunitiesDianaGray10

��

Unlocking DevOps Secuirty :Vault & KeylockHusseinMalikMammadli

��

Build with AI on Google Cloud Session #4Margaret Maynard-Reid

��

Understanding Traditional AI with Custom Vision & MuleSoft.pptxshyamraj55

��

TrustArc Webinar - Building your DPIA/PIA Program: Best Practices & TipsTrustArc

��

DealBook of Ukraine: 2025 edition | AVentures CapitalYevgen Sysoyev

��

Transform Your Future with Front-End Development TrainingVtechlabs

��

The Future of Repair: Transparent and Incremental by Botond DénesScyllaDB

��

UiPath Automation Developer Associate Training Series 2025 - Session 2DianaGray10

��

AIXMOOC 2.3 - Modelli di reti neurali con esperimenti di addestramentoAlessandro Bogliolo

��

Stronger Together: Combining Data Quality and Governance for Confident AI & A...Precisely

��

Unlock AI Creativity: Image Generation with DALL·EExpeed Software

��

Cloud of everything Tech of the 21 century in AviationAssem mousa

��

FinTech - US Annual Funding Report - 2024.pptxTracxn

��

UiPath Document Understanding - Generative AI and Active learning capabilitiesDianaGray10

��

Gojek Clone Multi-Service Super App.pptxV3cube

��

World Information Architecture Day 2025 - UX at a CrossroadsJoshua Randall

��

Google Fit, developer's view

1. Google Fit App Developer View Prepared for Personal Analytics Meetup By Gene Leybzon, Aug 2014

2. Applications That Can benefit from integration with Google Fit API Health/Fitness Data Collection Wearable Sensor-based apps Health/Fitness Behavior Analytics Statistical/Personal Analytics

3. What’s in Google Fit? Google Fit APIs Permissions/User Controls Data Store Sensor Framework

4. Google Fit Architecture

5. What’s defined in Android APIs? Sensor APIs (access to raw sensor data) Recording APIs (Subscriptions for data storage) History APIs (Bulk operations on recorded data)

6. Data flow from sensor to Fitness Store Sensors (Android or BTLE-connected) Sensor Adapters Fitness Recording API

7. Defined by Google Custom Custom Data Types

8. Examples of Data Types Defined by Google Name Description com.google.height User’s height [m] com.google.speed User’s speed [m/s] com.google.heart_rate.bpm Heart rate [beats per min] com.google.heart_rate.summary Max/Min/Average Heart rate [beats per min]

9. Creating Custom Data Types Create data type request using data type builder Invoke request using history API Check Result (asynchronously)

10. Working with fitness data Subscribe to fitness data List subscriptions Unsubscribe Start recording session Stop Recording session

11. Working with fitness history Read historical data Insert data set Delete data

12. Access to the row sensor data List data sources Register a new listener Unregister listener Scan available BT devices Claim BT device Release BT device

13. What is missing?  Structured data support for more data types  Local storage (on device)  More advanced data aggregation, statistical features  Support for other eco-systems (iOS)

Editor's Notes

#5: Fitness store is the cloud service
#6: Google defined two sets of APIs: - Android APIs - REST APIs

�ݺ�ߣ

Google Fit, developer's view

Recommended

More Related Content

Similar to Google Fit, developer's view (20)

Recently uploaded (20)

Google Fit, developer's view

Editor's Notes