Implementing AI
in the IoT-based
Healthcare App

ai in iot based healthcare app
overview ai in iot based healthcare app

Overview

IoT and AI together can definitely do wonders for your business. The Healthcare sector has already seen tremendous results with IoT and artificial intelligence, whether in mobile apps, performing surgeries, eliminating repeated tasks, and so much more. HData Systems created an AI and IoT-based mobile app solution to enhance working conditions and boost the employees' productivity.

Client Requirement

Our UK-based client is an expert in creating IT solutions for companies in multiple sectors. And he wanted to enhance his current business models by incorporating ultra-modern technologies to provide his team with better working conditions and boost their productivity to deliver better results. To create robust solutions, the client approached us to build them a model to process massive volumes of past data collected from IoT-based wearable devices and provide data-based notifications.

client requirements for ai in iot based healthcare app

Solutions

  • Our team began researching the current solutions, and AI experts examined what the current app had to offer and how they could further enhance it.

  • Our experts gathered data from the wearable devices and received the data as mentioned below:

  • Weather info

  • Driver's sex, age, and heart rate

  • Destination and route

  • Past data

  • Time of day

  • The collected data was inputted into the client's database for processing.

  • We instructed the ML model to perform several tasks:

  • Check health issues

  • Send alerts and suggestions to drivers

  • Create notifications

  • Evaluate drivers' health status

  • To create personalized alerts, our team used APNs to facilitate remote notifications.

Challenges

  • We were supposed to instruct an ML model to enhance the client's current solutions.

  • Our experts were asked to develop a model that can process large volumes of data from wearable gadgets and provide data-based notifications.

  • Moreover, this data wasn't adequate to analyze the health status; the current solution needed an extra ML-based model.

End-Result

  • Our team succeeded in delivering a machine learning model that merged AI and IoT to improve the client's healthcare app. The ML algorithms enabled data crunching and data-based notifications for iOS.

  • Moreover, the solutions facilitated the client to take better care of their staff, enhance the work environment for drivers, reduce health risks, and save money by automating real-time support services.

Technostack

postgresql
swift
python
aws
awslambda

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