Smart City
A design for future city
AP018 »
A city with IoT connectivity, autonomous car is a city of the future.
This project will try to accelerate network architecture search algorithm on FPGA which will usually take hours and even days on decent GPU.
Some of the project modules which are currently being worked on :
https://github.com/promach/gdas
https://github.com/promach/DDR
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.
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
Energy Waste Monitoring In The Home
AS022 »
Historical, realtime, and predictive measurement of the energy usage and waste within a home given acceptable ranges of temperature, lighting, etc. and correlating with the presence of, movement of, and absence of people and their respective needs for the environmental elements that draws power, uses resources, etc. From this, can determine the level of energy/resource efficiency of a given household. Can then be expanded to community, city, county, etc. scales.
Smart City
Energy efficient mixed-precision algorithm optimization for edge applications
AS024 »
Embedded intelligence applications must optimize the energy efficiency of their computational differentiation. IEEE-754 floating-point has been the workhorse for robust numerical computing, but is notoriously energy inefficient. Next-generation arithmetic solutions, such as posits and cfloats combined with user-defined rounding have demonstrated a 2-4x power benefit over IEEE-754. We have developed a mixed-precision algorithm design and optimization environment to deliver this technology to the marketplace in the form of custom applications and hardware accelerators. We'll use this platform for key SmartCity application such as collective intelligence and congestion optimization.
Smart City
Design
AP032 »
Cloud & azure
Smart City
FPGA BASED SMART TRAFFIC SYSTEM FOR SMART CITIES
AP033 »
Modern world having the issue to controlling the traffic at major cities for rapid increase in automobiles and also large time delays between traffic lights. So, in order to rectify this problem, we will go for different modes of traffic light control system. In this article, we have three modes i.e., Normal mode, Density mode, Emergency mode, IOT Mode.
Smart City
Project
AP039 »
hello
Smart City
Smart City Traffic Analyzer
AS027 »
A small form factor device for analyzing vehicle and pedestrian traffic using a computer vision workload running on the DE-10 Nano with local sensor data provided by the Analog Device plug-in board. The computer vision workload will be delivered using Azure IoT Edge and allow for extrapolating analytics to the cloud.
Smart City
Solar Follower
AS028 »
A sensor based solar farm that can be installed on top of a house.
Smart City
Fast Image Deblurring Reconstruction using Generative Adversarial Networks
AS032 »
Deblurring is the process of removing blurring entities from the image. In recent times, with the advent of machine learning there has been tremendous effort from the research community to come up with new deblurring techniques. However, the state-of-the-art deblurring technique still takes hours of time to construct proper deblurring effect. Therefore, in this project the objective is to construct proper deblurring image instantly. In order to accomplish that we will be using Generative Adversarial Networks (GAN). We have come up with a solution to speedup the GAN training. We will be deploying our solution into the cloud connectivity kit and also make use of Microsoft Azure, in order to generate accelerated deblurring image reconstruction.
Our project will have multiple applications starting from Smart City, Autonomous Vehicles, Industrial etc, as it involves creating proper visible images from blurring entities.