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
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
An FPGA-based Solution to monitor the Quality of Agriculture Produce
AP115 »
To minimize the losses that occurred during the storage process of farm produce (vegetables and fruits) by deploying sensor-based IoT technology to monitor and record essential and relevant parameters such as temperature, humidity, freshness indicators, etc.
This project will improve the profitability and customer satisfaction in the fresh produce industry and empower small-scale producers, shippers, and retailers with actionable data to optimize post-harvest inventory rotation and routing decisions.
Autonomous Vehicles
Autonomous Vehicle Speed Control on Heterogeneous Road ways
AP120 »
Road accidents have been very common in the present world, with the prime cause being careless driving and exceeding the speed limit. The necessity to check this has been very essential and different methods have been used so far. However, with the advancement in technology, different governing bodies are demanding some sort of computerised technology to control this problem of overspeed driving. Although all highways do have signboards indicating the maximum speed limit for the sake of the driver’s safety, people still do not obey the highway speed limit.
In this project, the speed of the vehicle is controlled through a continuous scanning of the signboards indicating the maximum speed limit on the roads and locking the maximum speed of the vehicle to the scanned value. By making use of a camera mounted to the vehicle pointing towards the left side of the road, the signboard image is captured. The camera captured an image of the speed limit signboard that was processed on the FPGA board for character recognition by using the optical character recognition (OCR) method. This value is compared with the database to lock the speed of the autonomous vehicle. The complete information of the autonomous vehicle with respect to speed maintained throughout the journey is monitored remotely over the IoT cloud for further enhancements and speed updates along the route.
Even in some areas where we do not find any speed limit boards, especially for these situations, we came up with an additional feature that consists of data pertaining to the speed of different vehicles in different types of lanes are not unique and classified based on the type of vehicle and carriage ways. As an illustration, for carriage type motor vehicles with no more than eight passengers, the maximum allowable speed on an expressway for plain terrain is 120km/h, where as it is 70km/h on municipal roads. Through such data, we propose a speed control system for controlled autonomous driving on any type of road and any type of terrain. The vehicle in which this control method is adopted initiates the journey with tracking using a GPS tracker provided in it. At the start of the journey, the user can select his/her destination point based on the estimated distance as well as the type of roads involved a priori. It shows what lanes are included in that path and respective vehicle speed limits saved as reference. If the vehicle finds any speed limit signboard on the journey, it compares with the data available. The priority for the database of the lines and respective speeds is given when there is no signboard in the way of a vehicle. This ensures the continuous control of the autonomous vehicle in both online and offline situations for all types of roads.
Data Management
R2A2: Runtime Reconfigurable Application Accelerator
AP121 »
With Moore's Law at its limits, one way of increasing compute capacity is Application Specific Hardware Acceleration; whereby a compute intensive problem is off-loaded to an Application Specific Processor - often called an ASIC - that leverages a specialized data-path to solve the problem much faster than a General Purpose Processor. (Examples are GPUs, Broadband Processors, AI acceleration chips etc.) Problem is, there can only be so many ASICs on a device deployed on edge. Also, ASICs are expensive to produce, and by nature, not reconfigurable.
The Goal of this project is to find a compromise between the expedient, but inflexible ASIC; and the versatile, but slow GPP. The R2A2 will use the Cyclone-V SoC, to realize a general-purpose, single-board, edge-deployable computer, which will run various compute intensive tasks of different resource load requirements. Depending upon the application running at a time, the R2A2 will configure the FPGA component of the Cyclone V SoC to act as an accelerator. This accelerator will be seen by Linux running on the SoC's ARM processor as a separate device, and a corresponding device driver, also loaded on the runtime will interface between the Processor and the FPGA.
By introducing runtime reconfigurable application-specific hardware, the R2A2 will help reduce carbon footprint by reducing global ASIC production requirements: This will eliminate potential e-waste down the years, while still providing high performance per-watt, which is desirable for computing on the edge. Also, high compute power on edge will lift bandwidth strain from the cloud/IoT infrastructure and reduce latency between the systems. Ideally, R2A2 will serve as a prototype for a plethora of Edge/IoT solutions utilizing FPGAs on SoCs for low cost, high flexibility, application specific operations.
Water Related
IOT based Smart Agriculture
AP122 »
The Continuously increasing demand of the food necessitates the rapid improvement in food production technology. In most of the developing countries, the national economy mainly depends on the Agriculture. But these countries do not able to make proper use of agricultural resources due to the high dependency on rain. Nowadays different irrigation systems are used to reduce the dependency of the rain and mostly the existing irrigation systems are driven by electrical power and manually ON or OFF scheduling controlled. The proposed system is usually designed for ensuring the proper level of water for growing up the plants all through the season. In addition, it provides maximum water usage efficiency by monitoring soil moistures at optimum level and it saves the electrical energy by turning off the motor when there is no water in the pump. The traditional methods are not efficient in controlling the illegal entry and it requires more labour work and time etc.
Smart City
Dumpyard Gas Monitoring System (DuGaMoS)
AP123 »
Existence of Toxic gases in huge dump yards and landfills has become a major concern in urban pockets. It leads to a lot of health issues, environment pollution and overall ecosystem damage. In order to address this problem we have come up with a solution of identifying or detecting the prevalence of toxic gases in these landfills. We propose to identify poisonous gases like Methane, Hydrogen Sulphide, Carbon Monoxide, Ammonia etc through an array of gas sensors integrated with Intel FPGA as the processor. Our target segment will be huge landfills and dump yards. We prefer to use Intel FPGA due to its parallel processing capabilities, extendable interfaces with several I/O ports, and high performance computing facility even with complex algorithms.
Other: Agriculture
Soil and Plant health monitoring through Smart Sensing and Monitoring System
AP124 »
Nowadays the major problems in Indian agriculture are small holdings, depleted soil and lack of easily driven systems to improve the yield at a large scale. In order to provide remedy for this issue,there is a need of a system which is easily accessible to monitor their plant health by providing data for their field conditions, humidity, pH level, water salinity and provide use full data about their plant. With the advent of recent developments in sensor technology and Embedded systems, its is possible to monitor the soil parameters and plant health. This research aims at providing assistance to the farmers for smart farming by developing smart IoT based real time systems for soil sensing and plant health monitoring. This proposed system measures the level of macro-nutrients present in the soil by using real time on the go technique. Further measured parameters are communicated to farmers in order to take decisions on water management, fertilizer utilization, crop selection and cultivation. In order to monitor the plant health ,the proposed system incorporates real time image acquisition and image processing techniques to detect the abnormalities on the surface of the leaves.
Smart City
Efficient method for automatic detection of door through sobel edge detector using fpga
AP126 »
Image Processing in its general form pertains to the alteration and analysis of pictorial information. The objective of image processing is to visually enhance or statistically evaluate some aspect of an Image not readily apparent in its original form. This processing is used for convenience in order to reduce the complexity faced during the operations performed on an image. Edge detection is one such branch of image processing used to detect the edges of the objects in a picture by calculation the difference in brightness of that edge pixel with its surrounding pixels using gradient method. In this project, Sobel operator is used as a filter for detection of edges of projection of a door without further increasing the already complex process of image processing. This is done using MATLAB, Sobel filter and FPGA.