Project Hub /Test & Measurement Instrumentation/Sensors & Signal Measurement Tools/Speech Recognition Based Beanbot - Beach Cleaning Robot

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ESP32

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Speech Recognition Based Beanbot - Beach Cleaning Robot

BEANBOT is a speech-recognition-controlled beach cleaning robot that sieves sand to collect debris into an onboard bin while sending live telemetry to ThingSpeak IoT cloud.

Originally published on CircuitDigest

View original tutorial

How It Works

The Speech Recognition Based Beanbot operates as an autonomous and voice-commanded beach cleaning platform powered by an integrated hardware ecosystem. At the core of the system is the Sipeed Maixduino board, which processes voice commands via the Maix_Speech_Recognition library and renders interface menus or visual feedback on the ST7789 video display. Power is delivered by a 3S 18650 battery bank protected by a 12V Battery Management System (BMS) and a 3A fuse. A USB-C to 12V battery booster charging module handles recharging, while a DC-DC converter steps down the 12V rail to 9V to power specific logic components safely. Motion control is achieved through two 12V 100rpm geared motors connected to BO wheels, driven via a 12V motor driver module that receives control signals from the microcontroller. For its specialized debris collection mechanism, the robot employs a 12V solenoid actuated by an IRF540N MOSFET solenoid drive circuit. An ultrasonic sensor is incorporated to monitor environmental proximity, allowing the robot to navigate the terrain while sieving sand and depositing collected waste into its onboard bin. System connectivity and remote cloud logging are supported via network libraries like WiFiEsp, enabling live data transmission.

Why Build This

Develop advanced undergraduate-level proficiency in integrating embedded AI speech recognition with multi-voltage power distribution systems.

Implement automated mechanical actuation using high-current components like DC gear motors and solenoids driven by discrete MOSFET circuits.

Deploy IoT-enabled robotics capable of addressing real-world environmental challenges such as automated coastal pollution mitigation.

Real-World Application

Large-scale periodic beach maintenance to combat pollution and protect marine and coastal environments without requiring massive manual manpower.

Skills You'll Learn

Embedded speech recognition integration

DC motor speed and direction control

MOSFET switching and solenoid driving

multi-stage power regulation and battery management

ultrasonic sensor navigation

IoT cloud telemetry

Safety Precautions

Includes a 3A fuse for load side protection and a Battery Management System (BMS) to guard against uneven discharging and short circuits.

Technology Tags

SPEECH RECOGNITION

IOT

THINGSPEAK

ULTRASONIC SENSOR

SOLENOID SIEVE

MOTOR DRIVER

LI-ION BATTERY

FUSION 360

3D PRINTING

C++

Frequently Asked Questions

How does the Sipeed Maixduino handle speech recognition locally?

The Maixduino board features specialized hardware architecture capable of running machine learning tasks locally using the Maix_Speech_Recognition library, eliminating the need for a constant cloud connection to interpret basic voice commands.

Why is a DC-DC converter required alongside the 12V BMS?

The 3S 18650 batteries supply a 12V nominal output to power heavy loads like the geared motors and solenoid, but a DC-DC step-down module is necessary to provide a stable 9V rail for sensitive logic and control circuitry.

What is the specific purpose of the IRF540N MOSFET in this build?

The microcontroller pins cannot directly supply the high current needed to actuate the 12V solenoid; the IRF540N acts as an electronic switch, allowing a low-control signal from the board to safely switch the high-current solenoid load.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

Kitkraft Project Hub — curated from the maker community, credited at the source.

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