Water Related
FPGA-based Irrigation System for Soft Fruit Farms
EM007 »
Prototype of an Intel FPGA-based automatic irrigation system for soft fruit farms in Perthshire, Angus and Fife, Scotland, UK
Autonomous Vehicles
AEB自动紧急制动系统
PR011 »
基于车侧的自动紧急制动系统，采用摄像头、毫米波雷达以及人体红外探测器为主要传感器，判断车辆前方出现的人以及其他生物，根据距离等情况进行决策是否进行制动动作。
Transportation
eego
AP021 »
With the world moving towards electric vehicles to combat the problem of emissions from vehicles, this project intends to build a battery based autonomous bot by adding AI to the bot with an emphasis on solar power along with battery management. Though there are a lot of organizations trying to contribute or gain value in the autonomous domain there is no single open project to understand and contribute to autonomous bots. This project intends to fill the gap by building a bot with AI and smart energy capabilities. The first level scope is to make the bot navigate by itself between two points in a defined environment i.e. L3 autonomy level and charge itself via solar power. This involves various sensor inputs for sensor fusion; wheel encoder for speed control, Object recognition for obstacles using camera, LiDAR for depth , RADAR for trajectory tracking and a powerful edge AI device for compute. The PID feedback control for the drive is difficult to achieve via software, so this will be developed on FPGA as well as any hardware acceleration ( RADAR data processing for instance) required for sensor fusion. Efficient solar power and battery management will also be targeted. Unknown obstacles will be reported to the cloud where models are trained ( by other bots as well in larger scope) and new models will be reloaded into the bot for better AI capabilities. Note: ROS is tentative for the sensor control, PID on FPGA for drive control, RADAR usage might be out of the scope based on availability of the sensor.
Smart City
Smart traffic light Control system Using FPGA
AP022 »
Now a days, controlling the traffic becomes major issue because of rapid
increase in automobiles and also because of large time delays between
traffic lights.
So, in order to rectify this problem, we will go for density based traffic
control system.
Smart City
Smart City Lightning (Street lighting)
EM008 »
This project is about building a Smart City Lightning System: Specifically streetlights for this particular project. Operating street lights are very necessary for security and safety in our communities and very costly as well. Sustainability when incorporated would improve efficiencies of the system in relation to its key objectives (security and safety) whilst cutting down cost as well. We focus on improving the efficiencies of streetlights for security and safety of our roads and cities in a smart approach. Explained below are some aspects of this project.
City cameras are almost found everywhere in our cities. The quality of these cameras is useless without proper street lighting. To do this, we include analog light sensors to read the brightness of the environment and allow the street light to give a certain brightness to improve illumination. The duration of day and night are also incorporated as well to deliver the right amount of lighting.
A sound reception device with trained machine learning models for different kinds of sound that depict a car crash, gun shot(s), intense noise (from human or not) indicating a variety of responses from a bad event would be incoporated as well. This concept would be applied, especially in areas where city cameras are around. Should in case a gunshot is heard, within a considerable radius in the surrounding, streetlights would be brightened to allow the city cameras have a better recording of the incident with and see how the shotter moves around when spotted in the city camera: This would be applied to other scenarios as well. In so doing, security agencies are alerted and this system would help them track the armed robbers or unwanted events as well (could be an accident, riot, etc).
All of the streetlights would be connected and inditcated on app with a map. This would help to indicate various conditions or states of the streetlights such as those that are down in real-time and need repairs, amongst others.
With regards to the above, the cost of operating streetlights would be controlled sustainably whilst improving efficiencies of streetlights for security and safety on our roads and cities.
An FPGA is ideal for this case since it is very fast and embraces parallel computing.
Water Related
River Water Surface Floating Material Monitoring System
PR012 »
River water surface floating object monitoring system uses sonar probe to transmit and receive sound waves as the front end of the system detection. When working, the master control device controls the sonar probe to transmit a certain frequency wave, when there is a floating object in a specific area, the wave transmitting forward meets the obstacle and will be reflected to the sonar probe, the master control device can calculate the distance s from the sonar probe to the floating object according to the time difference t from transmitting to receiving and the propagation speed v of the wave in the water, and the properties of the floating object can be judged by analyzing the difference between the return wave and the transmitting wave. At the same time, the main control device receives the information returned by the sonar probe, controls the camera device to shoot down the image of the specific area, and transmits all the above information to the cloud through the wireless transmission device. The function of monitoring floating objects on the water surface of the river is completed.
Smart City
Converter management system connected to the cloud (COMASYC)
AS009 »
Energy is a priority for humanity, in that sense, green energies are a necessity to satisfy the energy shortage and preserve the environment. So electronic converters play a key role.
A converter management system connected to the cloud controlled by a FPGA is proposed for applications in industry 4.0. It has capabilities to integrate panels solar arrays (PVs), batteries, loads at the same time with different converters according to user requirements. That means that the proposed system manages modulation, algorithms, collect information, and distribute energy.
For example, if the user requires a PV, then the P&O MPPPT algorithm is implemented to obtain the maximum energy in the PVs.
On the other hand, parameters such as energy consumption and production of each node are important for the redistribution of energy, for this reason, this model has a single brain that is connected to each node. So, a novel control is proposed based on load balancing managed by the cloud for high-priority requests. The cloud is the single brain that controls the system and organizes the flow power among nodes. The project is focused on the Peruvian reality for places where energy has to be a priority.
Water Related
Pool Purity
AS010 »
Swimming Pools provide the perfect evaluation testbed for monitoring and control of water chemistry. PH and Chlorine levels must be monitored and controlled for the health and safety of the swimmers. Given the destabilizing effects of solar exposure, air temperature, and rainfall, additional chemistry supports stabilizing the Chlorine and PH levels. Additionally, pumps circulate the pool water through filters which impact energy consumption. Using a 28 thousand gallon pool, we intend to demonstrate the use of FPGA’s for data collection and Cloud computing for control and monitoring of water chemistry processes. Stretch goals will include using weather forecasts to anticipate and hopefully minimize both chemical and energy usage.
Because other water applications have similar issues, this work will apply to other consumers; people, livestock, and agriculture are prime examples.
Marine Related
Artun Özdemir
AS011 »
Disabled
Smart City
Innova Qhawaq
AS012 »
Our project has as its main concept, the maximum use of energy through the efficient obtaining of renewable sources within the home, from photovoltaic energy through solar panels that move intelligently through neural networks that seek the maximum use of sunlight, harvesting energy obtained from strategic places such as doors, windows and the floor; and wind energy obtained efficiently through artificial intelligence and adapted to the environment. Through the use of the D10-nano FPGA as a data processing center where the information obtained from the sensors of these energy sources sends signals to actuators so that the energy is obtained more efficiently through the exact orientation where it is collected. as much energy as possible, making the fpga work as a decision-making center to control these actuators, and also by using data storage intelligently in the cloud, neural networks will be used to optimize energy collection from sources and optimize the use of resources.
Smart City
Reprogrammability Everywhere
AS013 »
FPGAs at the edge enable computationally intensive workloads to be performed with lower latency and lower total energy cost. They also enable custom functionality to be readily swapped and implemented. However, at the moment, FPGA configuration and deployment is not a very smooth and enjoyable as it could be. Compared to deploying a web application, generating and flashing an FPGA bitstream is manually intensive and hard to scale.
Using technologies like Azure IoT for device registration and enrolment, Azure Blob Storage for storing bitstreams, paired with a local Azure IoT client on the cloud connectivity kit and the Remote Update Intel FPGA IP, we will aim to develop a scalable, efficient, and easy-to-use "one click" bitstream deployment solution. With this we hope to enable the pervasive use of FPGAs in IoT deployments, with particular focus on smart cities.
In terms of demonstration, we will build a smart city proof of concept, to show that configuration and deployment of FPGA boards for traffic data collection (as one configuration), and weather and air conditions (as another configuration) can be robust (the system can support many deployments) and targeted (we can select individual boards).
Smart City
Self-Steering Pan-tilt Based on Sound Source Localization
PR013 »
Cardioid directivity microphone has good performance and is used in many scenarios, but it has to adjust its direction when the sound source moves. Or in a videoconferencing system, the camera always need to point to the speaker. Sound source localization (SSL) technology will be used as a guidance to control the pan-tilt carrying the microphone or the camera or something else to point to the sound source. Echo cancellation (EC) and beam forming (BF) will be used to enhance the signal quality. SSL, EC and BF technologies will be developed in Intel FPGA configured with a microphone array. Analog Devices plug-in boards will be used to control the motors for pan-tilt adjusting.