Smart Shoe for Elderly Tracking and Rescue with Piezoelectric Based Energy Harvesting System

The global elderly population is rapidly growing due to low birth rates and advances in medical technology. Most elderly people with dementia experience a loss of cognitive functions, such as thinking, emotional control, and memory, which interferes with their daily life and activities. Our research aims to develop a smart shoe for Elderly Tracking and Rescue System, consisting of two separate operations: the transmission unit and the receiving unit. In the transmission unit, a piezo-electric plate is placed in the shoe, generating energy through foot movement to power the system. This power drives the system to wirelessly transmit real-time location data using the low-energy ESP-Now communication protocol. In the receiving part, transmitted data is stored on a website with a graphical view, displaying location markers for easy visualization. Relatives can monitor the elderly person’s location by clicking on a marker, which opens Google Maps to show the exact position, enabling seamless and interactive tracking. Alerts are sent via SMS every 10 minutes to the elderly person’s relatives using a GSM module, including a Google Maps location link. Additionally, the GSM module ensures on-site data availability during power outages for uninterrupted operation. The system enhances the mobility and independence of elderly individuals through advanced technology, empowering them to move safely and confidently.

Introduction

The United Nations predicts that by 2025, there will be 1200 million elderly people worldwide, meaning that 15% of the population would be 60 years of age or older [1]. Over 15 million people in Bangladesh, and 6.90% of them are 60 years of age or older. According to projections, the proportion of the old population will rise from 6.05% in 1970 to 9.30% by 2025 [2].

To improve the lives of elderly people, there have been previous research contributions as follows. Turkmen and Celik [3] developed a piezoelectric shoe sole system using steel and aluminum frames under 50 kg–90 kg loads to analyze walking motion-to-electricity conversion. Izadgoshasb et al. [4], is designed a piezoelectric cantilever beam for motion energy harvesting, achieving peak efficiency at 70° using frequency up-conversion. Majeed et al. developed a method for harvesting energy from piezoelectric elements via daily movements [5], enabling fast lithium-ion battery charging for remote areas. Gogoi et al. [6] developed an autonomous shoe system that uses an accelerometer for gait sensing and piezoelectric elements to harvest energy from foot activities and operate the system. Ahmed et al. [7], designed a piezoelectric foot-pressure energy harvesting system for powering devices, with smart features like fall detection and activity monitoring. Vitorino et al. [8] examine the potential of a piezoelectric generator, activated by human gait, to power electronics in combat scenarios. Energy harvesting was tested using piezoelectric ceramics embedded in the sole of a soldier’s boot. Saranya et al. [9] developed an IoT-based footstep energy harvesting system that converts kinetic energy from human movement into usable electrical power. The author developed a system that generates electricity from footsteps using piezoelectric materials in [10], where an RFID module controls energy access for authorized users, allowing 60 seconds of power when a valid RFID tag is swiped. Zahid et al., [11] a footstep energy-harvesting system using piezoelectric sensors, a rectifier, voltage booster, and inverter to generate usable AC power. Ramakrishnappa et al. [12] developed a piezoelectric tile system that converts footsteps into electricity, with an Arduino circuit for voltage monitoring and battery charging. Vinisri et al. [13] developed a punching bag system with piezoelectric plates to convert strikes into electricity, using a battery, DC-DC booster, and rectifier for power storage and optimization.

The author developed a system that integrates piezoelectric sensors in shoe heels to capture foot impressions while walking or running [14]. It tracks movement and location, displaying data on an OLED screen or sending it to emergency contacts via GPS, activated by an SMS from a relative. Shanthini et al. [15] design a piezoelectric shoe generates electricity by converting mechanical pressure from walking and running into electrical energy using piezoelectric materials. Chava et al. [16] developed an IoT-based Smart Shoe and Glasses system for blind people, using obstacle detection and audio alerts for safer navigation. Manjunathan and Bhuvaneshwari [17] developed a smart shoe for the blind with ultrasonic obstacle detection, PIC-controlled vibrator (1 m–3 m range), and roadside presence indicator (red light). Anisha et al. [18] introduces a low-cost smart shoe for the visually impaired, capable of detecting obstacles and providing alerts via audio or vibration. Hamid et al. [19] developed a wireless insole system with four force sensors and an ESP32 to monitor real-time gait pressure, detecting abnormalities via ground reaction force analysis for rehabilitation. Pai et al. [20] designed a smart shoe for the blind, using accelerometers and pressure sensors to analyze gait patterns, foot swings, and pressure distribution in real-time. Mahalakshmi et al. [21] developed a smart system with ultrasonic/water sensors, piezoelectric, and solar panels for obstacle/damp detection, tactile feedback, and solar-powered operation, real-time Android alerts. Frontoni et al. [22], developed a system that presents an energy-harvesting shoe with polymer and ceramic piezo materials, generating power while walking. Ramzan et al. [23], developed a smart shoe for the blind, using sensors to detect obstacles/wet surfaces and alert wearers via buzzer and vibrations. Chehade et al. [24] developed smart shoes for the blind, detecting obstacles, wet floors, and falls with voice alerts and a mobile app for parental notifications and location tracking. Shelena et al. [25], designs a smart walking shoe for visually impaired individuals, integrating a moisture sensor, ultrasonic sensors, a button, DF Player, and speaker to provide smarter navigation and guidance. Wu et al. [26], developed a fall-detection system using an accelerometer and ultrasonic sensor, powered by a Li-ion battery, with emergency alerts via phone. Apoorva and George [27], developed smart shoes with FSR, IMU, and ultrasound sensors for gait analysis, controlled via Arduino. Gatto and Frontoni [28] developed a smart shoe with energy harvesting systems integrated into the soles. Using piezoelectric elements and electromagnetic induction, the shoes convert movement into electricity to power GPS devices and monitoring systems. Frontoni et al. [29] developed a piezoelectric energy harvesting apparatuses to power sensors and enable GPS localization. Gowthami et al. [30] developed smart shoes for the blind, integrating Google Maps, obstacle detection, and vibration-based navigation via a mobile app. Fan et al. developed smart shoes for the blind with a piezoelectric energy harvester that converts walking vibrations into electricity.

Previous research primarily focuses on using piezoelectric sensors in shoe heels for foot pressure detection but lacks analysis of current generation and power sufficiency for operational use. Additionally, no studies have explored integrating walking position monitoring into shoe systems. Our research focuses on tracking elderly people movement with a smart shoe, generating electricity from a piezoelectric plate in the shoe to power the system. Data is transmitted securely via the ESP-Now communication protocol to a server, where it is visualized on a website with real-time graphs and Google location markers. Relatives can monitor the person’s location live by clicking on the markers. Elderly individuals relative receive a safety alert SMS in every 10 minutes. Additionally, the GSM module provides on-site mobile network and data access during power outages, ensuring continuous operation. The system boosts elderly mobility and quality of life using advanced technology.

Research Method

System Block Diagram

The Transmitter Section of the Elderly people’s smart shoe, as demonstrated in Fig. 1, integrates an ESP Wi-Fi module, regulator, multiplier, battery, LED, and piezoelectric plate, which generates current as the elderly person walks. The piezoelectric plate generates current as the elderly person walks. Since the energy generated is AC, a regulator and multiplier convert it to a steady 3.3 V DC supply to power the electronic devices. The LED indicates that the piezoelectric plate is generating current. The ESP8266 transmits data to the receiver via the ESP-Now communication protocol, while the voltage multiplier provides power to the Wi-Fi module, and a Li-ion battery stores energy for extended circuit operation. GND and Vcc connected to the ESP8266’s 3.5 V. The GSM module’s TX and RX pins are connected to the ESP8266’s pins 29 and 30, respectively. The ESP8266 functions as the microcontroller, receiving data via the M2M ESP-Now communication protocol. The SIM800L GSM/GPRS module handles SMS and data communication using AT commands.

Fig. 1. Block diagram of the transmitter section.

The receiver, as demonstrated in Fig. 2, integrates the ESP8266 and a GSM SIM800L module. The ESP8266 serves as the system’s microcontroller, transmitting data to the receiver using the ESP-Now machine-to-machine communication protocol. The GSM module sends alert messages and ensures data availability on-site during power outages for uninterrupted operation.

Fig. 2. Block diagram of the receiver section.

Circuit Diagram of the System

In Fig. 3, the output from the piezoelectric plate allows current to flow in one direction through a diode, while a capacitor stores electrical charges as part of the voltage multiplier rectifier. The voltage multiplier rectifier output is fed to the voltage regulator input, which powers the ESP8266 Wi-Fi module to transmit signals to the receiver. This system uses piezoelectric plates to generate energy under foot pressure, with an ESP8266 as the main processor, transmitting data via the ESP-Now communication protocol. The generated energy flows through a voltage multiplier and rectifier to charge a battery, which powers the ESP8266 module at a steady 3.3 V through a regulator. In Fig. 4, the GSM module SIM800L is connected to the ESP8266 at the receiver end, with GND connected to GND and Vcc connected to the ESP8266’s 3.5 V. The GSM module’s TX and RX pins are connected to the ESP8266’s pins 29 and 30, respectively. The ESP8266 functions as the microcontroller, receiving data via the M2M ESP-Now communication protocol. The SIM800L GSM/GPRS module handles SMS and data communication using AT commands.

Fig. 3. Circuit diagram of transmitter section.

Fig. 4. Circuit diagram of receiver section.

System Work Flow Algorithm

In Fig. 5, the transmitter flow chart shows the process for the elderly tracking shoe system. As elderly people walk, a piezoelectric plate in the shoe generates current. This generated current is converted to DC using a voltage multiplier and is regulated by a voltage regulator to support battery charging and power the circuit. The ESP8266 then transmits data to the receiver using the ESP-Now machine- to-machine (M2M) communication protocol. In Fig. 6, the receiver flow chart demonstrates the operation of the system. The ESP8266 receives data transmitted from the transmitter and simultaneously stores them in a MySQL database on the server for further analysis. The system also sends an SMS update to the relatives of the elderly person every 10 minutes.

Fig. 5. Flowchart of the system (Transmission).

Fig. 6. Flowchart of the system (Receiver).

Implementation, Results and Discussion

The development of a Smart Shoe that detects foot pressure using a piezoelectric-based energy harvesting system, combined with advanced tracking and rescue capabilities, offers a novel solution for assisting quadriplegic patients. This system enables independent control, enhances the autonomy of elderly individuals, and revolutionizes assistive technology through sustainable energy utilization. The prototype’s development, system testing, and result analysis are all addressed in this section.

Prototype

An overview of the transmitter and receiver sections of the prototype is shown in Fig. 7, where the Smart Shoe for Elderly Tracking and Rescue demonstrates a piezoelectric-based energy harvesting system. In Fig. 7a, for understanding circuits, components are placed on a breadboard. The transmitter section converts walking energy into electrical current using a piezoelectric plate. This current is then converted into a stable DC output through a voltage multiplier and regulated to charge the battery and power the circuit. Simultaneously, the ESP8266 module sends data wirelessly via the ESP-Now communication protocol. In Fig. 7b, the receiver section shows the ESP8266 receiving data, logging it to a MySQL database for analysis, and sending SMS updates every 10 minutes to keep relatives informed of the elderly person’s location and movement.

Fig. 7. Shoe based energy harvesting system for elder: Transmitter (a) and Receiver section (b).

Transmitter (Breadboard Circuit)

Receiver

In Fig. 8, the system circuit is assembled on a Veroboard and integrated into a customized shoe for real-time implementation, specifically designed for elderly people. By constructing the circuit on a Veroboard, its functionality can be tested and verified in real time to ensure proper operation.

Fig. 8. System implementation (Veroboard circuit).

Result Analysis

In Figs. 9 and 10, the simulation and output without a smoothing capacitor are illustrated. The piezo-electric plate generates an AC signal with a frequency of 2 Hz and an amplitude of 5 V. This output is directed to a rectifier circuit using high-performance Schottky diodes for efficient conversion. While the rectifier provides a DC output, the voltage exhibits significant fluctuations due to the absence of a smoothing capacitor.

Fig. 9. Circuit diagram for simulation without capacitor.

Fig. 10. Simulation output for without capacitor circuit.

In Figs. 11 and 12, the simulation output with a smoothing capacitor is illustrated. Unlike the configuration without the capacitor, the addition of the capacitor results in a stable DC output. The capacitor effectively reduces voltage fluctuations, producing a smoother DC signal with significantly smaller ripple compared to the version without the capacitor.

Fig. 11. Circuit for simulation using capacitor.

Fig. 12. Output curve for simulation using capacitor.

Shoe’s performance depends on the capacitor’s performance. In Fig. 13, the performance analysis evaluates the output power and voltage across varying load resistances for three different capacitors: 10 µF, 100 µF, and 1000 µF. In Fig. 13a, the load resistance values of different capacitors vary with respect to output power. The figure demonstrates that the 10 µF capacitor delivers superior output power compared to the others. In Fig. 13b, the output voltage of different capacitors varies with respect to load resistance values. The analysis indicates that the 10µF capacitor’s output voltage is higher than those of the others. The analysis of different capacitors in the Smart Shoe system is shown in Fig. 14, where the output power and voltage are evaluated across varying load resistances for three capacitors. In Fig. 14a, the supply current changes with respect to load resistance, with the 10 µF capacitor exhibiting a higher supply current compared to the others. In Fig. 14b, illustrates the variation in load resistance for different capacitors and their corresponding efficiency. The performance analysis reveals that the 10µF capacitor achieves an efficiency of 83%, rather than other’s and it maximum.

Fig. 13. Performance analysis of differs capacitor: (a) Load resistance vs. output power, (b) Load resistance vs. output voltage.

Fig. 14. Different capacitor’s analysis: (a) Load resistance vs. supply current, (b) Load resistance vs. efficiency.

In Fig. 15, a unique graphical representation of the Smart Shoe system is presented, which illustrates the variation in DC voltage stored and charging time with changing load capacitance. This visualization highlights the efficiency of the system in energy harvesting and storage under different capacitance conditions.

Fig. 15. DC voltage stored and related charging time vs. load capacitance.

In Figs. 16 and 17, the oscilloscope output is demonstrated. The graphical representation shows the voltage waveform generated by the piezoelectric device, along with the output waveform displayed on the oscilloscope. The signal is then converted using the FFT function to reveal the frequency spectrum. In Fig. 16, the voltage output with steps is shown, representing the readings from the piezoelectric plate connected directly to the oscilloscope without any additional circuitry. In Fig. 17, the frequency spectrum of the output signal is displayed, providing insights into its frequency components.

Fig. 16. Oscilloscope visualization shows voltage generated by the piezoelectric plate with each step, without a voltage multiplier or full-wave rectifier.

Fig. 17. Frequency spectrum output without voltage multi-plier and full-wave rectifier.

In Figs. 18 and 19, display the oscilloscope output after passing through the voltage multiplier and full-wave rectifier, alongside the corresponding frequency spectrum of the output. Although the rectified signal is DC, it shows noticeable ripples, indicating that it is not a pure DC waveform. The frequency spectrum emphasizes these fluctuations. The comparison between the oscilloscope out-put and the CSV data, after simulation, highlights the effect of the rectifier. The rectifier converts the AC input to a pulsating DC, introducing ripples that differentiate the real time oscilloscope reading from the simulated output.

Fig. 18. Output visualization of the oscilloscope after passing through the voltage multiplier and Full wave rectifier.

Fig. 19. The frequency spectrum output after voltage multiplier and Full wave rectifier.

Elderly People Tracking and Rescue Website Visualization

A graphical representation of the website’s position markers is shown in Fig. 20. Real-time elderly positioning is displayed on a website with graphical visualization. A location marker provides pinpoint accuracy, offering a dynamic and intuitive view of their movements. This research stands out as it capitalizes on a frontend developed using HTML5, CSS3, and JavaScript, while leveraging Chart.js’s dynamic visualization features. Real-time web servers are operated by Node.js with a backend, enabling seamless integration of MySQL databases with scalable network applications. This ensures an accurate portrayal of locations on the website. The exact positioning of the elderly person’s location on Google Maps is shown in Fig. 21, which can be precisely displayed by clicking on the server’s graphical location pin. The proposed system features an innovative graphical user interface for navigation positioning.

Fig. 20. Website map view with geographical markers.

Fig. 21. Accurate map location of the elderly people.

Website Visualization Battery Status

In Fig. 22 illustrates the analysis of battery life and operational time through website visualizations. The graphical interface displays real-time battery status, including charging and discharging cycles, with hourly updates throughout the day.

Fig. 22. Real time Website status: Battery charging and discharging status (Hourly in a day).

Per-Step System Output Power Generation

In Fig. 23 shows the output power measured in milliwatts (mW) vs resistance graph.

Fig. 23. Output power generated in milliwatts (mW).

SMS Notification

In Fig. 24 illustrates the system’s SMS notification. In Table I, the system’s operation is compared with that of previous research.

Fig. 24. SMS notification.

Table I. Comparison Analysis of Available Research

Paper ID	Alert	Website	Mobile	SMS	Generated power
[3]	No	No	No	No	1.43 mW
[4]	No	No	No	No	2.7 mW
[5]	No	Yes	No	No	–
[6]	No	No	No	Yes	0.56 mW
[7]	No	Yes	No	No	–
[8]	No	No	No	Yes	0.87 mW
[9]	No	No	No	No	8.34 mW
[10]	No	No	Yes	No	–
[11]	No	No	No	No	–
[12]	No	No	Yes	No	–
[13]	No	No	Yes	No	–
[14]	SMS	No	Yes	No	–
[15]	No	No	Yes	No	–
[16]	Buzzer	No	Yes	No	–
[17]	LED	Yes	No	No	–
[18]	Audio	Yes	Yes	No	–
[19]	No	No	No	No	–
[20]	No	No	No	No	–
[21]	No	No	No	No	–
[22]	No	No	No	No	–
[23]	Voice	No	No	No	–
[24]	Voice	No	No	No	–
[25]	Voice	No	No	No	–
[26]	No	No	No	No	–
[27]	No	No	No	No	–
[28]	SMS	No	No	No	–
[29]	No	No	No	No	–
[30]	No	No	No	No	–
[31]	No	No	No	No	0.35 mW
Propose	SMS	Yes	Yes	Yes	184.42 mW

Transmission of Data

ESP-NOW enables peer-to-peer communication between two devices, allowing them to exchange data directly with minimal power consumption, without relying on traditional Wi-Fi networks. Successful ESP-NOW transmissions consume between 600 mw and 660 mW of power, while WiFi transmissions consistently peak at 950 mW. This represents a power reduction of over 30% compared to WiFi, highlighting ESP-NOW’s energy efficiency [31].

Conclusion

Our research introduces a smart shoe that generates electricity through energy harvesting, enabling real-time tracking and rescue of elderly individuals. The system powers low-energy devices and operates fully autonomously. The per-step generated power is 184.42 mW. Future enhancements will focus on a machine learning algorithm for data analysis and smooth operation.