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The Integrations of Ideas to promote waste reduction and improve quality of lifes
🌱Mission of the project🌱
🌱Mission of the project🌱
The project's mission is to integrated IoT,hydroponic and microbubbles generator to produce an automated environmental-friendly system. This system allows all range of community to familiarize with waste reduction and promote IoT simultaneously.
🤖Prototype
🤖Prototype
🎥Videos🎥
🎥Videos🎥
Time Lapse for fabrication of prototype
Briefing of the project
⚡Parts & Sensors⚡
⚡Parts & Sensors⚡
🧬Dissolved Oxygen Level in solution
🧬Dissolved Oxygen Level in solution
Optical Character Recognition(OCR)
Oxygen level in solution is kept between 7.0 mg/L and 10.0 mg/L
Measured by dissolved oxygen sensor.
Data acquisition done by using Optical Character Recognition (OCR) through OpenCV.
The recognition tool used is Windows Hello Face Recognize Webcam.
🧬Ambient temperature & Humidity
🧬Ambient temperature & Humidity
Temeperature & Humidity Sensor (DHT11)
12V DC fan
Relative humidity is kept between 50% and 70%.
Measured by DHT11 sensor.
Controlled by Pulse Width Modulation(PWM) of 12V DC fan.
🧬Light Intensity
🧬Light Intensity
The light intensity kept between 50 and 200 reading from sensor.
Measured by DFR0026 ambient light sensor.
Controlled by PWM of 12V led lights.
LED lights is on for 16 hours and off for 8 hours.
🧬Nutrient Flow Input
🧬Nutrient Flow Input
Input manually by user through Blynk Apps.
User can choose the volume of nutrient to be feeded into hydroponic tank.
Actuated by DC pump.
🧬Water Level
🧬Water Level
To prevent the overflow of hydroponic solution, water level float switch is used.
Water flow from water reservoir is controlled by solenoid valve.
📱Software📱
📱Software📱
Live streaming of hydroponic system in any web browser through Flask web framework
Data monitoring of hydroponic system through Blynk apps
💻User's Interface💻
💻User's Interface💻
🔬Design of Microbubble Nozzle🔬
🔬Design of Microbubble Nozzle🔬
Using 3D printer to fabricate Microbubble Nozzle
Microbubbles nozzle installed into system
Design of the Microbubble nozzle using Solidworks
🚀Applicability 🚀
🚀Applicability 🚀
Enhance development in smart hydroponic ,microbubble generator studies
Expansion of knowledge in applying Internet of Things(IoT),Machine Learning, Big Data & Cloud Computing
🌚Credits🌚
🌚Credits🌚
Mok Chik Ming, Yap Yee Doung, Liong Wei Xuan, Tan Zhi Yong
❓ Q&A❓
❓ Q&A❓
How Temperature & Humidity Sensor (DHT11) works?
How Temperature & Humidity Sensor (DHT11) works?
The DHT11 is a basic, ultra low-cost digital temperature and humidity sensor. It uses a capacitive humidity sensor and a thermistor to measure the surrounding air, and spits out a digital signal on the data pin (no analog input pins needed). Its fairly simple to use, but requires careful timing to grab data. You can get new data from it once every 2 seconds, so when using the library from Adafruit, sensor readings can be up to 2 seconds old.
Comes with a 4.7K or 10K resistor, which you will want to use as a pullup from the data pin to VCC.
How dissolved oxygen sensor works?
How dissolved oxygen sensor works?
The sensor is considered as electrochemical dissolved oxygen sensors. In an electrochemical Dissolved Oxygen sensor, dissolved oxygen diffuses from the sample across an oxygen permeable membrane and into the sensor. Once inside the sensor, the oxygen undergoes a chemical reduction reaction, which produces an electrical signal. This signal can be read by a dissolved oxygen instrument.
What is Pulse Width Modulation(PWM) and how it works?
What is Pulse Width Modulation(PWM) and how it works?
How Optical Character Recognition(OCR) works?
How Optical Character Recognition(OCR) works?
Optical Character Recognition involves the detection of text content on images and translation of the images to encoded text that the computer can easily understand. An image containing text is scanned and analyzed in order to identify the characters in it. Upon identification, the character is converted to machine-encoded text.
How is it really achieved? To us, text on an image is easily discernible and we are able to detect characters and read the text, but to a computer, it is all a series of dots.
The image is first scanned and the text and graphics elements are converted into a bitmap, which is essentially a matrix of black and white dots. The image is then pre-processed where the brightness and contrast are adjusted to enhance the accuracy of the process.
The image is now split into zones identifying the areas of interest such as where the images or text are and this helps kickoff the extraction process. The areas containing text can now be broken down further into lines and words and characters and now the software is able to match the characters through comparison and various detection algorithms. The final result is the text in the image that we're given.
The process may not be 100% accurate and might need human intervention to correct some elements that were not scanned correctly. Error correction can also be achieved using a dictionary or even Natural Language Processing (NLP).
The output can now be converted to other mediums such as word documents, PDFs, or even audio content through text-to-speech technologies.
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