This mobile app is the brainchild of a working mother of two. She had to turn down a stellar career opportunity because of scheduling issues between her work and her kids' various extracurriculars as she struggled to find an affordable nanny who could also drive her children to their activities.
Thus, she identified the need for safe, reliable, and affordable transportation for school-aged children and solved it by establishing her own kid-focused ridesharing service.
The simplest way to materialize this idea was to create a taxi-hailing app where parents would book and track a ride, another app where the drivers would receive their bookings, and a central admin dashboard where our client's Ride and Safety Monitoring team would manage everything.
Our taxi-booking app development team had to implement the following attributes in the applications.
We assembled a team of two web developers, two Flutter developers, and one quality analyst. The client's challenges were tackled through different tools. The entire solution was built on with functional counterparts for the iOS and Android mobile environments.
To enable real-time tracking of drivers, we use GeoLocation API to retrieve their location at 40-second intervals and to upload updated location data to a server. This data is then integrated and accessible in the parents' app and the admin solution.
We integrated using method channels for Android & iOS to record driving behavior events such as hard braking, rapid acceleration, phone use while driving, hard cornering, and even collisions. This data goes into the admin solution and is tracked to ensure children's safety during rides.
Our mobile app developers integrated the in this solution to ensure that the drivers get information about a user's location, real-time traffic data, and turn-by-turn navigation, thus allowing seamless pick-ups and drop-offs through the best routes.
To determine the estimated time for every ride, we integrated the into this app. This API is fed with ride origin and destination values, and it returns travel time and distance data for the recommended routes. This ETA is shown to drivers and parents.
Using the data recorded by Zendrive, our team deployed a ride-fare algorithm to calculate the time between the beginning and end of the ride, wait-times (if any), and delays. This data is further used to determine exact cost for the ride in real-time.
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