Description:FIELD OF THE INVENTION

The present invention relates to the field of biomedical sensing, Internet of Things (IoT), artificial intelligence-based health monitoring systems, and micro-electromechanical systems (MEMS).

More particularly, the invention relates to a micro-cantilever based smart sensing architecture integrated with AI and IoT communication modules for continuous remote healthcare monitoring and physiological signal detection.

BACKGROUND OF THE INVENTION

Healthcare monitoring systems are increasingly shifting toward real-time, remote, and intelligent diagnostic solutions. Conventional monitoring devices such as wearable sensors and hospital diagnostic equipment often suffer from limitations including: Limited sensitivity, Bulky hardware, High power consumption, Lack of continuous remote monitoring, Limited integration with AI-based decision systems.

Micro-cantilever sensors, commonly used in MEMS technology, provide high sensitivity for detecting mechanical, biological, and chemical variations. However, most existing systems utilize micro-cantilever sensors only for laboratory analysis rather than integrated AI-IoT based real-time healthcare monitoring. Therefore, there is a need for an integrated micro-cantilever sensing platform capable of real-time physiological signal detection, wireless communication, and intelligent cloud-based analysis. The present invention addresses these limitations by introducing a micro-cantilever-based AI-enabled IoT healthcare monitoring architecture.

OBJECTIVES OF THE INVENTION
• The primary objective of the present invention is to develop a micro-cantilever based intelligent healthcare monitoring system capable of detecting physiological signals with high sensitivity and transmitting the data through an IoT communication network for real-time analysis.
• Another objective of the invention is to integrate micro-electromechanical systems (MEMS) based micro-cantilever sensors with artificial intelligence algorithms for automated health condition monitoring and early detection of abnormalities.
• A further objective of the invention is to design a piezoelectric transduction mechanism using materials such as Zinc Oxide (ZnO) or Lead Zirconate Titanate (PZT) to convert mechanical deformation of the cantilever into measurable electrical signals.
• Another objective is to develop an efficient signal conditioning and analog-to-digital conversion system capable of accurately processing weak electrical signals generated from the micro-cantilever sensor.
• A further objective of the invention is to enable wireless communication between the sensing device and cloud servers through IoT gateway architecture, allowing remote monitoring of patient health conditions.
• Another objective is to provide a compact, low-power, and cost-effective sensing architecture suitable for wearable healthcare devices and smart medical monitoring systems.
• Another objective of the invention is to enhance the sensitivity of the cantilever structure by structural optimization techniques such as circular hole formation and material layer modification.
• A further objective of the invention is to provide real-time visualization and monitoring of physiological data through web dashboards or mobile applications, enabling doctors and caregivers to access patient information remotely.

NOVELTY OF THE INVENTION
The present invention introduces a novel integrated healthcare monitoring architecture that combines micro-cantilever MEMS sensing technology with artificial intelligence and Internet of Things (IoT) communication frameworks.
The novelty of the invention lies in the following aspects:

1. Integrated MEMS-AI-IoT Healthcare Architecture
Unlike conventional health monitoring devices that rely only on wearable sensors or isolated sensing modules, the proposed invention integrates:
• Micro-cantilever MEMS sensor
• AI-based data analysis
• IoT communication infrastructure
• Cloud-based health monitoring
This integrated architecture enables real-time intelligent healthcare monitoring.

2. Piezoelectric Cantilever Based Physiological Signal Detection
The invention utilizes piezoelectric materials such as ZnO and PZT integrated within the micro-cantilever structure to convert mechanical displacement caused by physiological interactions into electrical signals with high sensitivity.
This provides ultra-sensitive detection capability compared to conventional biosensors.

3. Structural Optimization of Micro-Cantilever
The cantilever structure incorporates circular holes and optimized material layers, which significantly increase displacement sensitivity and improve signal generation efficiency.
Such structural modification enhances the mechanical response and sensing performance of the device.

4. Intelligent Cloud-Based Health Monitoring
The invention integrates AI algorithms in cloud servers to analyze physiological signals received from the sensor system. The AI engine performs:
• pattern recognition
• anomaly detection
• predictive health analysis
This allows early detection of potential health abnormalities.

5. Real-Time Remote Healthcare Monitoring
The invention enables continuous remote monitoring of patients through IoT communication modules, allowing data transmission to healthcare professionals through mobile applications or web dashboards.
This significantly improves telemedicine and smart healthcare infrastructure.

DESCRIPTION

SUMMARY OF THE INVENTION

The present invention provides a smart healthcare monitoring system based on micro-cantilever sensing technology integrated with artificial intelligence and IoT communication frameworks.

The system includes:
• A micro-cantilever sensing module
• A piezoelectric transduction mechanism
• Signal conditioning circuits
• Analog-to-digital conversion unit
• Microcontroller unit (MCU)
• Wireless communication module
• Cloud-based data processing platform
• AI-driven health analysis engine
• User interface for monitoring

The micro-cantilever sensor detects physiological changes such as pressure, vibration, biomolecular interaction, or mechanical deformation. These signals are converted into electrical signals using piezoelectric materials such as ZnO or PZT.
The processed signals are transmitted through an IoT communication gateway to cloud servers, where AI algorithms analyse health data in real time.
The system enables:
• Continuous patient monitoring
• Remote diagnostics
• Early detection of abnormalities
• Low power operation
• High sensitivity biomedical sensing

DETAILED DESCRIPTION OF THE INVENTION

1. System Architecture
The proposed system consists of multiple interconnected modules forming a micro-cantilever based intelligent healthcare monitoring architecture.
The architecture includes:
1. Power source and voltage regulator
2. Micro-cantilever sensing element
3. Signal conditioning module
4. Analog-to-Digital Converter (ADC)
5. Wireless communication module
6. Microcontroller Unit (MCU)
7. IoT gateway
8. Cloud server
9. AI analysis module
10. User interface dashboard
The sensing mechanism operates by detecting external applied force or biological interaction on the micro-cantilever surface, causing mechanical displacement.

2. Micro-Cantilever Sensing Mechanism
The micro-cantilever structure consists of:
• Fixed end
• Free end
• Layered materials
• Sensing surface
The cantilever beam bends when external force or biological interaction occurs on its top surface. The displacement generated is proportional to the applied force.

3.Piezoelectric Transduction Layer

The cantilever includes a piezoelectric material layer such as Zinc Oxide (ZnO) or Lead Zirconate Titanate (PZT-5H).
When the cantilever bends:
Mechanical deformation → generates electrical voltage.
This voltage acts as the primary sensing signal.

4. Signal Conditioning
The generated electrical signal is typically weak and therefore requires amplification and filtering.
The signal conditioning stage includes:
• Operational amplifier
• Noise filter
• Gain control circuit
This stage prepares the signal for digital conversion.

5. Analog-to-Digital Conversion
The conditioned analog signal is converted into digital data using an ADC module integrated with the system. This allows digital processing by the microcontroller.

6. Wireless Communication
The processed data is transmitted through a wireless communication module, which may include:
• Wi-Fi
• Bluetooth Low Energy
• ZigBee
• LoRa
The wireless transmitter sends the data to an IoT gateway.

7. Cloud Processing and AI Analysis
The IoT gateway forwards the data to a cloud server where artificial intelligence algorithms analyze physiological signals.
AI models detect:
• Abnormal health conditions
• Pressure anomalies
• Biological interaction patterns
• Early disease indicators

8. User Interface
The processed information is displayed through:
• Mobile application
• Web dashboard
• Healthcare monitoring system
Doctors and patients can monitor real-time health data remotely.

9. Structural Optimization of Cantilever
Several structural modifications improve sensing performance.
Hole Optimization
Circular holes are introduced into the cantilever to:
• Reduce stiffness
• Increase sensitivity
• Improve displacement characteristics
Material Optimization
Materials such as:
• PDMS
• ZnO
• PZT-5H
• Silicon substrate
are used to optimize mechanical and electrical performance.

ADVANTAGES OF THE INVENTION

The present invention offers several advantages:
1. Ultra-sensitive micro-cantilever sensing
2. Real-time health monitoring
3. AI-based medical diagnosis
4. Remote IoT connectivity
5. Low power consumption
6. Compact MEMS-based structure
7. Early disease detection capability
8. Scalable healthcare monitoring architecture
9. High signal accuracy
10. Cloud-based patient monitoring

, Claims:CLAIMS

Claim 1
A micro-cantilever-based healthcare monitoring system comprising:
• a sensing cantilever structure,
• a piezoelectric transduction layer,
• a signal conditioning circuit,
• an analog-to-digital converter,
• a microcontroller unit,
• a wireless communication module,
• an IoT gateway,
• a cloud server, and
• an artificial intelligence analysis engine,
wherein the cantilever structure detects physiological signals and transmits processed data for remote healthcare monitoring.

Claim 2
The system according to claim 1, wherein the micro-cantilever includes a piezoelectric material selected from ZnO, PZT, or PDMS-based structures.

Claim 3
The system according to claim 1, wherein the cantilever structure includes circular holes for sensitivity enhancement.

Claim 4
The system according to claim 1, wherein the signal conditioning module comprises amplifiers and filters for noise reduction and signal enhancement.

Claim 5
The system according to claim 1, wherein the wireless communication module supports Wi-Fi, Bluetooth, ZigBee, or LoRa protocols.

Claim 6
The system according to claim 1, wherein artificial intelligence algorithms analyze the sensor data for health anomaly detection.

Claim 7
The system according to claim 1, wherein the cantilever displacement generates electrical potential proportional to applied physiological force.

Claim 8
The system according to claim 1, wherein the cloud platform provides real-time monitoring through a mobile or web interface.