Smart City
Waste Management Monitoring System
AP103 »
This project is about a smart bin that can detect whether the bin is full or not. The status of each bin will be informed to the collector so that he can collect the bins which are full according to the sensor data.
Transportation
IOT SOLUTION ON FPGA
AP104 »
Image Processing is used to modify pictures to
improve their quality and extract structured information. The
need to process them in real time has lead to implement them
in hardware. To implement image processing algorithms using
high level languages requires thousands of lines of code which is
inefficient as it takes more time. Alternate solution is using Xilinx
System Generator, which is a modeling tool where design is
captured by using xilinx blockset from library environment. The
main advantage of system generator is Xilinx blocksets provide
close integration with MATLAB Simulink that helps in cosimulating FPGA module with pixel vector provided by
MATLAB Simulink blocks. The image analysis plays an
important role in medical imaging. This paper provides image
analysis of a CT scan image. The algorithms are performed on an
image to extract significant features such as image enhancement,
contrast stretching, negative of image, image segmentation and
detecting the edges for a CT scan image. The area and power
parameters are evaluated using reconfigurable platform -Artix-7
FPGA.
Marine Related
Float-E: Surface Water Oil-Collecting Robot
AP105 »
The potential risk for large-scale oil spills to occur can lead to devastating results, causing both environmental and economic damages that can take several years to clean up and recover. With the existence of offshore rigs and the constant transportation of oil around the world each year, more autonomous and efficient ways of handling these impacts were explored. This project proposes a semi-autonomous robot to alleviate the problem, exploring the use of image processing to locate and collect these hazardous spills; making use of a pump to collect and store these spills into an oil container; coconut husk as a more cost-effective solution to filtering the oil from excess water. In addition, the fabrication method touches on 3D printable parts combined with PVC pipes that act as pontoons to keep the robot afloat.
Aside from utilizing the provided FPGA Cloud Connectivity Kit and Microsoft Azure IoT, a variety of software tools were used to ensure the feasibility of the robot’s main components; SolidWorks, to calculate and guarantee the proper buoyancy and stability of the design; CoppeliaSim, to demonstrate the robot's pathfinding and obstacle avoidance through three environments, no obstacles, static objects, and dynamic obstacles; Arduino, for the actuation and mobility of the robot; Python in designing the oil detection system using HSV color space and Haar Cascade; user interface platform, created in PyQt5, to enable user interaction in controlling the oil detection and manual movements of the device. The coordinates of the oil are sent to the Arduino via serial communication; once the Arduino receives the data, it adjusts the DC and servo motors depending on the x and y values; this includes the LED light to simulate the vacuum. Moreover, experimentations made on coconut husks were to ensure that oil may be filtered out from the water. In the development of a semi-autonomous surface water oil-skimming robot through various means of simulation and experimentation, it can be utilized to substitute manual labor to clean a body of water by having the robot device collect and store the optimal amount of oil in a locomotive manner.
Other: AGRICULTURE
SOIL MONITORING BOT FOR SMART AGRICULTURE
AP106 »
Agriculture plays the major role in economics and survival of people in India. The purpose of this project is to provide embedded based system for soil monitoring and irrigation to reduce the manual monitoring of the field and get the information via mobile application. The system is proposed to help the farmers to increase the agricultural production. The soil is tested using various sensors such as NPK sensor, pH sensor, temperature sensor, and humidity sensor. Based on the result, the farmers can cultivate the appropriate crop that suits the soil. The obtained sensor values are sent to the database through Wi-Fi router and date and time is noted in the database and also a notification message is sent.
Smart City
ABC
AP107 »
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Autonomous Vehicles
ABC
AP108 »
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Smart City
IoT Pollution Box System with ML Processing
AP109 »
With climate change showing real and measurable effect on our daily lives with increase in extreme natural calamities, planning for a sustainable future has become a nessasity. To solve a problem of this scale, one needs to understand it fully first. To understand the extent of our effect on a climate a easy to use and distribute measuring units will be crucial. We will be tacking this problem.
A end-to-end Pollution Detection system with Machine Learning Predictions will be designed. It will consists of two major part. Client-Side Pollution Box which will be compact and fully integrated with various sensors and modules to detect Air, Water, Light, Noise Pollution Parameters and Server-Side Cloud Processing Center which will use ML based systems to find patterns and correlations between various pollution parameter and how they are affected with weather conditions. The project will provide a easy to replicate system which can be used by concerned authorities in the Metropolitan areas to monitor and curb pollution on a real-time basis.
Pollution Box will contain a Camera, Microphone, Air Quality and Gas Sensor, Water TDS and Turbidity sensor, which will be used to create a Holistic Pollution Parameter which will be used to build a fully contained pollution index.
Camera will be used to scan the night sky and provide a light pollution metric which can be used to further plan the areas street light consumption. Microphone will be used to provide a all-day look at the noise pollution and can issue mental health warning if exceeding the researched paramter. Air Quality and Gas Sensors can be used to provide a accurate Air Quality Index. Whereas resistivity based TDS calculation can identify increase in toxicity and salinty of water on a real-time basis.
Making the Pollution box compact and easy to use will make it easier for the authorities to make a mesh of these IoT enabled boxes that can give a better resolution in detecting the problem areas and solving the issue at a larger scale and thus ensuring the sustainble future.
At the server end the data will be processed and Machine Learning based program will find patterns and correlation between different parameters to further our understanding on the effects of pollution.
Other: Agriculture related
Assessment of seed quality using image processing with fpga
AP110 »
We are going to check the quality of the seed using image processing. We will use fpga and interface the camera with it to get the output.
Food Related
Sustainable Mushroom Farming
AP111 »
In Malaysia, mushroom cultivation activity has been long existed. Mushrooms have been identified as one of the high-value commodities under Malaysia’s National Agro Food Policy (2011-2020). The government recognizes the mushroom industry to have a potential to be developed as demand is increasing in tandem with the increase in population and consumption. Currently, the cultivation activity is growing and thriving due to high demand in Malaysian market. The consumption of mushrooms per capita has been expected to increase from 1.0 kg in 2008 to 2.4 kg in 2020. Besides, there were 648 mushroom entrepreneurs in Peninsular Malaysia in 2008. The higher demand together with the supports from government to improve this industry in future, has gave an opportunity to entrepreneurs to keep venturing in this area. The demand of mushroom is increasing but in Malaysia, the number of cultivators and production is decreasing. This is due to the inconsistent environmental condition with high temperature of 32–35 °C and low humidity of 60%–70%.
Humidity and temperature affect on fruiting body of oyster mushroom. Optimal temperature and humidity is known as 13-16°C and > 80%. High and low temperature indicates > 16°C and < 12°C, respectively and high and low humidity indicates > 80% and < 60%. The morphology of the mushroom depends on the humidity and temperature. Oyster mushroom also can grow at moderate temperature ranging from 20℃ to 30 ℃.
In Malaysia, some studies have been conducted and results show that in a room temperature, the optimum humidity should be larger than 90% in order to get the optimum growth and yield of mushroom. Due to the high demand in our country and also in the world, the industry requires high technology that uses less labour but produces higher productivity. Hence, electronic based monitoring system should be developed to maintain the humidity as high as 90% at room temperature and the data must be sent to cloud for further development. Mushroom farmers can view the temperature and humidity data remotely and watering process can be done automatically to maintain the humidity. Information or database is also important since the number of mushroom entrepreneurs keep increasing due to the demand and support from government. Besides the hardware, the software also should be developed to ensure that the mushroom industry will be sustained and growing. The Graphical User Interface (GUI) must be attractive and informative since it will be a medium of communication among the mushroom entrepreneurs, mushroom farmers and government agency.
Food Related
Sustainable Mushroom Farming
AP112 »
In Malaysia, mushroom cultivation activity has been long existed. Mushrooms have been identified as one of the high-value commodities under Malaysia’s National Agro Food Policy (2011-2020). The government recognizes the mushroom industry to have a potential to be developed as demand is increasing in tandem with the increase in population and consumption. Currently, the cultivation activity is growing and thriving due to high demand in Malaysian market. The consumption of mushrooms per capita has been expected to increase from 1.0 kg in 2008 to 2.4 kg in 2020. Besides, there were 648 mushroom entrepreneurs in Peninsular Malaysia in 2008. The higher demand together with the supports from government to improve this industry in future, has gave an opportunity to entrepreneurs to keep venturing in this area. The demand of mushroom is increasing but in Malaysia, the number of cultivators and production is decreasing. This is due to the inconsistent environmental condition with high temperature of 32–35 °C and low humidity of 60%–70%.
Humidity and temperature affect on fruiting body of oyster mushroom. Optimal temperature and humidity is known as 13-16°C and > 80%. High and low temperature indicates > 16°C and < 12°C, respectively and high and low humidity indicates > 80% and < 60%. The morphology of the mushroom depends on the humidity and temperature. Oyster mushroom also can grow at moderate temperature ranging from 20℃ to 30 ℃.
In Malaysia, some studies have been conducted and results show that in a room temperature, the optimum humidity should be larger than 90% in order to get the optimum growth and yield of mushroom. Due to the high demand in our country and also in the world, the industry requires high technology that uses less labour but produces higher productivity. Hence, electronic based monitoring system should be developed to maintain the humidity as high as 90% at room temperature and the data must be sent to cloud for further development. Mushroom farmers can view the temperature and humidity data remotely and watering process can be done automatically to maintain the humidity. Information or database is also important since the number of mushroom entrepreneurs keep increasing due to the demand and support from government. Besides the hardware, the software also should be developed to ensure that the mushroom industry will be sustained and growing. The Graphical User Interface (GUI) must be attractive and informative since it will be a medium of communication among the mushroom entrepreneurs, mushroom farmers and government agency.
Other
FPGA based Smart Watering System for indoor and agricultural plants
AP113 »
The goal of this project is to develop a smart monitoring and watering system for plants that records various factors that help plants survive. The idea behind this is to use FPGA and hence a hardware description language (HDL) along with the sensors that collect data in accordance with the change of weather and soil moisture levels. The project also provides the future scope of maintaining a gardening system precisely using FPGA boards and can also be deployed to understand different crop trends using different sensors.
Food Related
Test Project
AP114 »
Test Project