Our Case Studies

Blockchain and IOT based Pill Dispensing Devices 

This case study highlights Softlabs Group's collaboration with a South Korean company to create a cutting-edge platform using Blockchain and IoT for monitoring patient medication compliance more effectively in clinical trials. By tackling challenges like designing a compact, durable pill dispensing bottle and ensuring secure data management, the project led to improved patient engagement and set a new standard in healthcare technology.

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Industry

Medical & Healthcare

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App Type

Enterprise

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Methodology

Agile Scrum

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Platform

Android, IOS

Client Intro

Softlabs Group embarked on a pioneering project with a South Korean company to develop an innovative platform leveraging Blockchain technology and IoT-connected Pill Dispensing Bottles.

This initiative aimed to enhance patient compliance monitoring during clinical trials and treatments, offering a modern solution to a traditional healthcare challenge.

Country

country flagSouth Korea

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The Need for Innovation


01
Market Growth

The golf training aids market is projected to grow from $0.55B in 2024 to $0.76B by 2033, showing strong demand for innovation.

04
Static Tools

The healthcare industry has long faced challenges in ensuring patient compliance with medication regimens, especially in controlled environments like clinical trials.

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02
Demand for Personalization

Traditional methods often rely on self-reporting or indirect monitoring, which can lead to inaccuracies and affect the reliability of trial outcomes.

03
Solution Gap

The need for a more accurate, tamper-proof, and user-friendly approach led to the exploration of integrating Blockchain and IoT technologies to create a real-time monitoring solution for dose compliance.

What we Built

As the AI and software development partner for OnePuttPro, we engineered a compact, intelligent golf putting device that delivers real-time insights through precise motion tracking and seamless mobile integration.

The solution leverages Attitude and Heading Reference System (AHRS) and Human Activity Recognition (HAR) technologies to capture stroke data, analyze technique and provide instant, actionable feedback through a dedicated mobile app.

We developed the system using a combination of hardware components—including an accelerometer, gyroscope, microcontroller, and camera module—paired with a custom-built app designed for intuitive use, personalized coaching and performance tracking.

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Client Pain Points and Fixes


Challenges Client Faced

  • 01
    Designing a Compact, Long-lasting Device

    Creating a small-sized pill dispensing bottle with a durable battery life capable of providing real-time updates.

  • 02
    Ensuring Accurate Pill Count Tracking

    Accurately counting and reporting the number of pills dispensed through IoT sensors.

  • 03
    Secure Data Management

    Safely storing and managing sensitive patient data on the Blockchain, ensuring privacy and accessibility.

  • 04
    Firmware Reliability

    Developing firmware that is not only reliable but also capable of delivering detailed diagnostics to maintain device performance.

How We Solved It

  • Developed Compact IoT-Connected Bottles

    Designed and engineered pill dispensing bottles with embedded IoT sensors for accurate pill count tracking.

  • Implemented Blockchain Technology

    Utilized Blockchain for secure and immutable record-keeping of dispensing data, enhancing data integrity and patient privacy.

  • Optimized Firmware for Performance

    Crafted firmware specifically tailored to manage power efficiently while ensuring continuous, reliable performance and data transmission.

  • Companion Mobile App Integration

    Created a mobile app that receives real-time data from the IoT bottles, providing an intuitive interface for both patients and healthcare providers.

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What we Achieved

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1
Enhanced Medication Compliance Monitoring

Provided a reliable method to monitor patient compliance with medication regimens in real time.

2
Secure and Transparent Record-Keeping

Achieved secure, tamper-proof record-keeping of medication dispensing data, building trust in clinical trial processes.

3
Improved Patient Engagement

The easy-to-use platform encouraged patient engagement and adherence to medication schedules.

4
Innovative Healthcare Solution

Established a new benchmark for integrating technology in healthcare, specifically in the context of clinical trials and patient treatment.

AI Features
Implemented

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IoT-Connected Pill Dispensing Bottles

Bottles equipped with sensors to accurately monitor and record each dispensing action.

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Blockchain-Based Data Storage

Leveraged Blockchain technology for secure, immutable storage of dispensing data, accessible only to authorized personnel.

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Energy-Efficient Firmware

Developed firmware that optimizes battery usage, ensuring long-term, reliable performance of the pill bottles.

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User-Friendly Mobile Application

A companion app that provides patients and healthcare providers with real-time access to dispensing data, enhancing the monitoring process.

This Solution also Fits for


Swing Sports

Swing Analysis in Sports like Baseball, Cricket, Tennis or Badminton.

Injury Control

Injury Prevention Through Movement Monitoring.

Performance Boost

Athletic Performance Optimization in Track & Field.

Virtual Motion

Motion Tracking in eSports and VR-Based Fitness Games.

Balance Training

Training Posture & Balance in Gymnastics or Martial Arts.

Technologies Used

Android
Android Native

Android Native

Swift

Swift

React JS

React JS

Backend
Net

.Net

msSQL

msSQL

Nodejs

Nodejs

AI
Pytorch

Pytorch

Tensorflow-lite

Tensorflow-lite

20+

Years of Experienced

25+

Countries

2000+

Clients

5000+

Projects

Other Case Studies


At Softlabs Group, we take pride in solving complex business challenges with innovative and reliable solutions. Our case studies showcase how we’ve empowered clients across industries with tailored software that delivers measurable results and drives success.

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FAQs


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We use industry-standard evaluation metrics (e.g., precision, recall, F1-score) and iterative validation to ensure high accuracy. We also run stress tests in real-world environments and continuously improve models based on live data.

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