SmartIV is an IoT-powered system that monitors IV drip flow rates in real time, sends automated alerts to nurses, and prevents critical medication errors — reducing patient risk and easing the burden on healthcare staff.
Reduction in
missed IV alerts
Flow rate
monitoring
Automated
nurse alerts
Low bag alert — Bed 07-B: Estimated empty in 18 minutes. Nurse notified.
IV-related incidents occur due to delayed nurse response to drip completion
Of manual gravity-led IV infusions deviate from the prescribed drop rate by over 20%, causing dangerous dosing errors.
Average shift length for a nurse, during which dozens of IV bags must be monitored
Automates monitoring and alerts — so nurses focus on care, not checking drips
Intravenous therapy is one of the most common procedures in hospitals. Yet in most wards, nurses must manually check each IV drip bag to determine flow rate and volume — a repetitive, error-prone process that is easy to miss during busy shifts.
When a drip runs dry unnoticed, air can enter the bloodstream. If the flow rate is incorrect, patients may receive too much or too little medication — with potentially life-threatening consequences.
SmartIV combines hardware sensors, cloud infrastructure, and a mobile-first interface to deliver complete IV drip oversight.
Optical drop sensors count drip rate continuously and stream data to the cloud for instant visibility on any device.
Push notifications are sent directly to nurses' devices when a bag is nearly empty, flow is abnormal, or the drip has stopped unexpectedly.
Nurses input the initial bag volume via the device keypad. The system continuously calculates the remaining volume and time until empty based on the exact number of drops detected by the dual IR sensors.
Nurses and ward managers can monitor all patients in real time through a clean mobile app or desktop dashboard, from anywhere in the hospital.
Every IV session is logged. Doctors and administrators can review flow rate histories, alert logs, and trend data for quality improvement.
All patient and session data is encrypted in transit and at rest. Role-based access ensures only authorised staff can view sensitive records.
A layered architecture connecting bedside hardware to the cloud and nurse interfaces.
The SmartIV unit attaches directly to the IV stand — compact, non-invasive, and battery-powered for full ward portability.
Two IR sensors accurately count drops passing through the IV drip chamber, ensuring precise real-time flow rate calculations and reliable redundancy.
Acts as the system's actuator, precisely compressing or releasing the IV tube to regulate the fluid flow rate autonomously.
Allows nurses to manually input the initial IV bag volume (e.g., 500mL) and view real-time status, alerts, and settings directly at the bedside.
An ESP32 microcontroller in the edge device handles local processing, motor control, and sensing. A second ESP32 acts as a USB dongle connected to the desktop station for reliable local data reception.
Rechargeable Li-Po battery with a BMS ensures the unit runs independently of mains power, supporting full ward mobility.
All components integrated onto a custom-designed PCB for a compact, reliable, and production-ready form factor.
SmartIV's software stack delivers real-time monitoring, instant alerts, and historical insights across mobile and desktop.
All patients on a ward displayed on a single screen with current flow rate, volume, and estimated time remaining.
Nurses receive immediate push alerts when a bag is low, the drip has stopped, or the flow rate is outside normal range.
Full log of each IV session per patient including flow rate graphs, alert events, and administration timestamps.
Nurses, ward sisters, and admins each have differentiated views and permissions to keep data secure and relevant.
Nurses can acknowledge alerts directly in the app, creating an audit trail of response actions per patient event.
Mobile app (iOS & Android)
Desktop app frontend
Desktop native backend
Device cloud gateway
Local database
IoT messaging layer
SmartIV is tested at every layer to ensure reliability, accuracy, and real-world readiness.
Drop sensor accuracy testing against known flow rates
Stepper motor precision and automated flow regulation accuracy
Battery life and power management under continuous operation
Wi-Fi connectivity and MQTT data transmission reliability
Device performance in hospital temperature and humidity conditions
Unit testing for all backend API endpoints and business logic
Integration testing: hardware → MQTT → backend → mobile app
Load testing simulating full ward with 20+ simultaneous devices
User acceptance testing with nursing staff at a hospital
Alert delivery latency — target under 3 seconds from sensor trigger
| # | Item | Model / Notes | Qty | Unit Price (LKR) | Total (LKR) |
|---|---|---|---|---|---|
| 1 | Primary MCU | ESP32-S3 Development Board | 1 | 2,150.00 | 2,150.00 |
| 2 | Secondary MCU | ESP32 DevKit V1 | 1 | 1,835.00 | 1,835.00 |
| 3 | Stepper Motor | NEMA 17 Stepper (Bipolar) | 1 | 2,240.00 | 2,240.00 |
| 4 | Motor Driver | TMC2208 Silent Driver | 1 | 1,390.00 | 1,390.00 |
| 5 | UI Display Module | Arduino LCD + Logic Level Converter | 1 | 1,950.00 | 1,950.00 |
| 6 | Input Peripherals | 4x4 Keypad Module + Buttons | — | — | 820.00 |
| 7 | Drop Detection | IR Speed sensor module LM393 | 1 | 150.00 | 150.00 |
| 8 | Main Power Supply | WX-DC2412 Switching Power Module | 1 | 2,950.00 | 2,950.00 |
| 9 | Battery System | 2x 18650 Cells + Holder + BMS | 1 | — | 1,305.00 |
| 10 | Voltage Regulation | Buck convertor + Protective Cover | 1 | 300.00 | 300.00 |
| 11 | Medical Testing Kit | Standard IV sets (x3) + NaCl IV bags (x4) | — | — | 1,258.08 |
| 12 | Chassis | 3D Injection moulding | 1 | 5,000.00 | 5,000.00 |
| 13 | Alert System | Buzzer | 1 | 55.00 | 55.00 |
| 14 | Misc. Hardware | PCBs, Screws, Bearings & Connections | 1 | 4,820.00 | 4,820.00 |
| Total Estimated Hardware Cost (per unit) | LKR 26,223.08 | ||||
* Prices are estimates based on local market rates. Cloud hosting and software development costs are separate.
Lecturer, Department of Computer Engineering
Faculty of Engineering, University of Peradeniya
Senior Lecturer, Department of Computer Engineering
Faculty of Engineering, University of Peradeniya
Professor, Department of Nursing, Faculty of Allied Health Sciences, University of Peradeniya
A visual log of our prototyping phases and competition highlights.
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Highlights from our participation as finalists in the SLIoT Challenge and future events.
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SmartIV monitoring station for Windows.
Note: Windows SmartScreen may appear since this is a research project installer. Click More info → Run anyway.
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