IoT Project

IoT Health Monitoring System

A wearable vitals monitor that streams heart rate, SpO2 and temperature to a dashboard with threshold alerts.

Intermediate7–9 weeksCSE · IT · MCAInternet of ThingsEmbedded Systems

Project overview

A wearable node measures pulse, blood oxygen saturation and body temperature, transmits readings to the cloud, and alerts a caregiver when a value crosses a configured threshold. A dashboard shows live values and history for review.

The engineering interest is in signal quality — filtering motion artefacts, discarding implausible readings, and deciding when a threshold crossing is real rather than noise.

Problem statement

Patients recovering at home and elderly people living alone are monitored only during periodic visits. A deterioration between visits goes unnoticed until it becomes an emergency.

Proposed solution

Sample vitals continuously on a low-power wearable, filter the signal on the device, transmit summarised readings rather than raw samples to save power and bandwidth, and apply alert rules in the cloud with a confirmation window to avoid false alarms.

Key features

  • Continuous pulse and SpO2 measurement from an optical sensor
  • Body temperature measurement with a contact sensor
  • On-device filtering and rejection of implausible readings
  • Configurable per-patient alert thresholds
  • Alert confirmation window so a single spike does not trigger a call
  • Caregiver notification by app, SMS or email
  • History charts with daily and weekly views
  • Battery level reporting and low-power sleep between samples

Technology stack

Hardware

ESP32MAX30100 / MAX30102 pulse oximeterDS18B20 temperature sensorOLED displayLiPo battery

Firmware

Arduino frameworkMoving average filteringDeep sleep scheduling

Cloud

Firebase Realtime DatabaseNode.js alert serviceSMS gateway

Client

Flutter or ReactRecharts

System architecture

The flow below is what goes into your architecture diagram and the corresponding chapter of the report.

  1. Sensor sampling runs in a timed loop with the display updated locally
  2. Filtering stage removes motion artefacts and out-of-range values
  3. Aggregation computes a stable value per interval instead of streaming raw samples
  4. Transmission publishes the summarised reading with a device and patient identifier
  5. Alert service evaluates thresholds with a confirmation window
  6. Dashboard renders live values, trends and the alert history

Expected output

  • Working wearable prototype with a live dashboard
  • Vitals history with daily and weekly trend charts
  • Alert log with the triggering readings recorded
  • Battery life measurement at the chosen sampling interval

Suitable branches, difficulty and duration

Suitable branches

Difficulty level

Intermediate. Comfortable for a team where at least one member has worked in this stack before.

Development duration

7–9 weeks including documentation, tested and ready to demonstrate. Milestones are planned around your review dates.

Documentation, review, demo and viva support

Documentation support

Abstract, problem statement, literature survey guidance, system architecture, ER and UML diagrams, module descriptions, test cases and screenshots — prepared in your department format.

Project review support

Delivery is split across your review calendar so review one has a design and plan, review two has working modules, and the final review has the integrated, tested system.

Demo support

A rehearsed demo path, seeded sample data, a reset script, and a recorded walkthrough kept as a backup in case something fails in the review room.

Viva preparation

A written question bank for this domain, a code walkthrough session, and practice at explaining each module in your own words — because the examiner will ask you.

Customisation options

Colleges reject duplicate topics, so most projects are adjusted before we start. These are the usual directions for this one.

  • Add ECG capture with an AD8232 module for richer cardiac data
  • Add fall detection using the accelerometer
  • Add a medication reminder that pairs with the companion app
  • Add anomaly detection that learns a patient's normal range over time
Talk to CodeLab69

Enquire about the IoT Health Monitoring System project

Send your branch, college and first review date. You will get confirmation of scope, what the customisation would look like, and a delivery plan mapped to your reviews.