Social Network App For Runners

  • Mobile Application

A social network app for runners is an application that helps running enthusiasts connect with each other and share information about running. Additionally, it helps runners to find groups to join, find running partners, and find running events. It can also be used to track individual runners’ progress, find mentors, and join groups based on a specific interest in running. Many social networking apps are designed specifically for those who engage in physical activity or sports; however, there is no specific social network app devoted exclusively to runners. Also when a runner completes a workout, they are able to choose to share the workout with the group or to keep it private. Additionally, runners can message other runners in the group. communicate with one another, find running partners, and find running events. Additionally, it is convenient and helpful. We developed an app for athletes and runners to socialize with like-minded people near them. The targeted audience of the app is mainly the runners and sports community, so the app can match you to similar runners in your local area. With the help of a smart algorithm, it can match you up with other runners in your area based on your skills, goals, and workout style. This app can be considered a “one-stop place” for all matters of running, coaching, club/race events, and interactive chats between runners and people passionate about sports.

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The Challenge

To develop a social networking mobile app for sports people with the help of some smart matching algorithms and fitness trackers, we were asked to create a social networking medium by utilizing the data from multiple fitness trackers used by the users. One of the core functionalities is to develop a user matching algorithm based on the user location, running style, running route, running schedule, etc., which helps in finding the best companion runners. The Objectives: A mobile application for Android and iOS has to be developed with the following main considerations: Collecting data from multiple fitness trackers via SDKs and APIs. Helping people to connect with each other and practice running or sport better through a matching algorithm. Create a social network medium for sports people by providing them an option to share their experience and running statistics with other runners. For communication between app users, one-to-one chat & group chat features needed to be added.

iLeaf's Process


We discuss to ensure that we have the exact idea of what is required


There's regular interaction with the client to ensure things are on track


Begins according to the needs of our client


The final output will be a perfect match to our clients requirement

Tracker SDKs & APIs: The most challenging part here was the data collection and management from the multiple trackers. We have integrated almost a dozen of popular fitness trackers into the app with the help of SDKs and provided APIs. Some of the trackers didn’t have any data exporting mechanism, hence we utilized some third-party solutions. Crone Jobs & Webhooks: The next challenge we faced was keeping the user’s data on our database updated all the time. We could reduce the workload of our servers by utilizing the webhooks provided by some of the third-party trackers. On the other hand, we had to rely on the Cron jobs that communicate with the tracker servers. Matching Algorithm: Based on the data we collected from trackers, we came up with an advanced yet smart algorithm to help find the most appropriate runners. We utilized the user’s running schedules, routes, running pace, running time, running distance, and other similar parameters for finding the best matches. Chat Feature: Like any other social media app, we too had the chat feature. For integrating chat functionality we opted for our own chat solutions. We set up a dedicated server for running Openfire which uses the XMPP protocol for instant messages. Our chat feature also has every feature included in a chat application like user presence, read receipts, chat histories and etc. Technologies Used: Swift for iOS and Java/Kotlin for Android. Laravel for backend and APIs Combined use of MySQL and MongoDB for database XMPP for chat AWS S3 Cloud Storage ElasticSearch for quick search Mixpanel for analytics Firebase Test Lab/Device Farm – QA testing

The Result

By using the app, the community could arouse the interest of its young members in sports. They could create a strong sports community and host events for their members. The App has inspired many users to find new people, socialize better, and create a larger sports network. Even though the app development was quite challenging, the application indeed proved the efforts made by the entire team.

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