This project shows an IoT Weather and Health Monitoring System based on the Raspberry Pi Pico W to

monitor essential health parameters and environmental factors in real-time. It includes a BME280 sensor for

temperature, humidity, and pressure, an MQ135 sensor for monitoring air quality, a Ds18b20 body temperature

measurements. An OLED screen offers in-device feedback, and IoT connectivity along with a GSM module

upgrades could involve AI-powered predictive analytics, integration with mobile health apps, and cloud data

logging for long-term trend identification and enhanced emergency response.

The development of Internet of Things (IoT) technology has made it possible to create smart health and

environmental monitoring systems that offer real-time access to data and alerting capabilities. This work

describes an IoT Weather and Health Monitoring System based on the Raspberry Pi Pico W, intended to

monitor environmental factors like temperature, humidity, pressure, and air quality in real-time, and vital health

weather conditions, MQ135 for air quality, MAX30100 for pulse oximeter, and MAX30205 for body

This paper addresses the hardware implementation of the system, integration with IoT, and real-time alerting

mechanisms, followed by a comparative study with current models. Future improvements, including AI-driven

predictive analytics and integration with mobile health apps, are also discussed to enhance the accuracy and

usability of the device.

Using the ESP32 microcontroller, Dey and Bera created an Internet of Things system that gathers

physiological and environmental data, including temperature, humidity, and heart rate, and sends it over Wi-Fi

to a cloud server [1]. The system's main strength is in educational settings, where it provides a hands-on

introduction to embedded systems and sensor integration, even though it enables applications like fitness

tracking and home automation. The ESP32 is a good choice for multipurpose Internet of Things devices

continuous and real-time data to identify health issues early on. It can be used in remote healthcare

applications because of its wireless connection and low power consumption.

A mobile-based health self-monitoring system designed to assist patients in tracking and reporting their health

condition, was introduced by Yusuf et al. [4]. In order to enhance illness prevention and control, the system

enables synchronization between patients and medical providers and shows patient data graphically.

In order to measure meteorological factors such as temperature and humidity, Qasim et al. proposed an Internet

of Things-based weather monitoring system that makes use of the ESP32 and Blynk platform [5]. The system

highlights the benefits of real-time analysis and visualization of data via cloud-based transmission and

visualization, as well as its possible application in environmental forecasting, aviation, and agriculture.

The Raspberry Pi Pico W is the brain of this IoT-based weather and health monitoring system, responsible for

real-time processing of sensor data and communication. It has a dual-core ARM Cortex-M0+ processor and

integrated WiFi allowing end-to-end IoT integration for remote monitoring. The Pico W gathers readings from

the BME280 (pressure, temperature, humidity), MQ135 (air quality), MAX30205 (body temperature), and

high fever, poor air quality, or lack of oxygen trigger SMS notifications from a GSM module. Its low power

requirements, multiple I/O pins, and wireless feature make it suited for portable real-time environmental and

health monitoring uses in remote or urban locations.

Fig 1. Pico W Pin Diagram

which would be beneficial for outdoor enthusiasts, hikers, and people with respiratory ailments.

Fig 2. BME Environmental Sensor

The GY-MAX30102 is a high-accuracy optical sensor employed in this IoT-based health and weather

monitoring system to track heart rate, SpO₂ (blood oxygen saturation level), and the intensity of the pulse. It

uses photoplethysmography (PPG), where infrared and red light-emitting diodes (LEDs) measure changes in the

blood flow. The sensor is connected to the Raspberry Pi Pico W through I²C, which delivers efficient real-time

health tracking. Its power consumption is low, which makes it suitable for portable and wearable devices. In this

project, the GY-MAX30102 facilitates the measurement of oxygen levels, particularly in high-altitude or

The DS18B20 is a digital temperature sensor utilized in this weather and health monitoring IoT-based system to

capture accurate body or ambient temperature. It talks to the Raspberry Pi Pico W through the 1-Wire protocol,

making it possible to use multiple sensors on one data line. It has a range of -55°C to 125°C and accuracy of

±0.5°C, which provides accurate readings. In this project, the DS18B20 assists in tracking body temperature for

fever detection and cross-references environmental conditions from the BME280 sensor. Through its

integration, real-time alarms for high fever or extreme ambient temperatures are enhanced, providing increased

health and safety monitoring.

Fig 4. DS18B20

patients with respiratory or cardiovascular diseases.

Fig 5. MQ135 Sensor

emergency messages for conditions like high fever, poor air quality, or oxygen deficiency. This ensures users

receive alerts even in areas without internet access, making the system ideal for remote health and

environmental monitoring applications.

Fig 6. GSM Module

OLED display is a key part of the IoT-based weather and health monitoring system, offering real-time visual

Fig 7. OLED Display

The MQ-2 gas sensor is a general-purpose low-cost sensor employed for the detection of various gases such as

smoke, methane, LPG, and hydrogen. For this IoT weather and health monitoring project, the MQ-2 can be

utilized as another environmental sensor to aid in air quality measurement. It detects a change in the

concentration of gas and gives an analog output signal readable by the Raspberry Pi Pico W. Including the

MQ-2 makes it possible to sense the potential toxic gas leakage or smoke status, offering alerts for safety with

other environmental feedback. When gas concentrations reach a specified level, the system can provide alerts

on the OLED screen and issue real-time alerts through GSM or IoT platforms, enhancing the device's

capability to detect air quality in sensitive environments.

sensors (BME280, MQ135, and GY-MAX30102) that are interfaced to the Raspberry Pi Pico W. Utilizing the

Pico W's built-in Wi-Fi, the device can function as a local HTTP server, allowing the app to retrieve data

Because of its ease of use, quick iteration cycle, and compliance with online and cloud APIs, MIT App

life, and user reaction are all meticulously followed in the design process. Continuous data analysis and long-

The Raspberry Pi Pico W, the brains behind the Internet of Things-based weather and health monitoring

system, collects and analyzes real-time sensor data. The BME280 measures temperature, humidity, pressure,

The hardware architecture of an Internet of Things-enabled weather and health monitoring system built on the

applications. Under typical circumstances, the OLED dynamically shows sensor data in real time, enhancing

situational awareness and usability. Together, the local visualization and the GSM module's remote monitoring

QUALITY" of about 91 suggests a somewhat safe air quality, whereas a value of "GAS: YES" indicates the