Other: Forest Conservation
FPGA based Internet Of Trees for Smart Forest
AP027 »
Forest fire has become one of the big challenges in recent days. Even with the highly evolved technology, we are struggling to avoid forest fire. Forest fire is causing plenty of loss to the vegetation and animals habitats.
Internet Of Trees is an FPGA based system, which shall be used for collect the data of environmental conditions, early fire detection, animal conservation, tree conservation in the forest.
CNN Algorithm will be running on the FPGA board, which will process the image to identify the fire.
when the fire is detected, the auxiliary circuit of the smoke detection/Co2 level sensor will be used to confirm the detection is not false detection.
This camera-based system also will be used to monitor the animal movements, image-based tree statistics, rain data. Using analog sensor boards we can detect the environmental conditions.
Microsoft Azure will be used to deploy analytics algorithm and cloud software. Using Microsoft Azure we also deploy warning systems to firefighters, Real-time video monitoring systems on the cloud.
By deploying CNN-based sensor applications using FPGA accelerates the detection speed, Accuracy of the detection, and ease of connection to the cloud.
Food Related
Development of Intelligent Food Supply Chain Management System
AP028 »
This project proposal presents an Intelligent Food Supply Chain Management System for covering from field to end-user. This project is based principally on THREE (3) different application areas such as Food Plantation, Food Warehouse, and Food Transportation using a smart intelligent system. This system seeks to support and to reduce food waste by improving the reliability of the technology from manual detection to automated detection system designed especially for real-time monitoring using IoT implementation on growth and maturity level of fruits in the Food Plantation, classification of fruits grading in the Food Warehouse and also fruits controlling and tracking during Food Transportation operation. The system is implemented on a FPGA-SoC Intel Cyclone V SoC available on DE10-Nano Kit, Microsoft Azure, and Analogue Devices module to acquire the sensors reading and control the actuators to maintain the suitable environment in three different application areas. The proposed system has high-performance requirements covered by FPGA-SoC since it has concurrency and low power consumption, making it suitable for this intelligent food supply chain management system in smart agriculture applications.
Industrial
AI IOT Driven CNC Machine optimisation
AP029 »
Using an FPGA to improve the motion control of CNC machines under dynamic loading.
Other: General Processor
General Purpose Neural Processing Unit
AP031 »
[The General Purpose Neural Processor Unit proposed in this project aims to simulate and cluster an SNN-based neural network that can solve at least one problem.]
There is a saying, butterfly effect. This means that the small wings of butterflies drive a big typhoon. Likewise, something happens under the influence of many things. For example, solar power generation is affected by wind, cloud, temperature, etc., and farming is affected by solar radiation, precipitation, and temperature. To solve these nonlinear problems, methods such as machine learning have emerged these days.
Machine learning is an algorithm that uses neural networks to analyze data and make decisions based on learned information. Since various types of data can be used as data for learning, it is suitable and widely used to solve nonlinear problems. However, it has only recently begun to be used because it requires a lot of computing power. And even now, big models take a lot of time.
As a way to solve this problem, a neural network model was designed and uploaded to the FPGA for use. But one neural network model had the disadvantage of being able to solve only one problem. To this end, accelerators such as NPUs equipped with many modules that perform repeated operations (mainly convolution operations) also came out.
These NPUs were created with neural networks such as CNN and RNN, which are second-generation neural networks. However, research on SNN, a third-generation neural network, is active these days, and NPU using it is being designed. A typical example is IBM's Truenorth. SNN is a neural network that mimics real neurons and has several advantages in terms of power and learning. In addition, SNN is completely bio-plausible, so it is an essential route in the future to implement artificial intelligence.
Several neurons gather to create a neural network system, and the system gathers to form a neural network network. As things happen under the influence of many things, data on many things are important. Each task is proposed as an idea to break away from not the basic way provided to the neural network as a variable and but solve it through network connection and cluster.
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
Automatic recycling system for residential units
AP034 »
Our team introduces an automatic classification system for wastes.
If garbage is not classified, it can cause environmental problems, and if it is classified well, resources can be saved through recycling.
Our system can classify not only good-conditioned garbage (plastic, cans, bottles, etc.), but also bad-conditioned garbage.
Data Management
Image and Video Upscaling and Downscaling using FPGA
AP035 »
With time the rate at which we are producing data is increasing at a very tremendous rate. And it seems that this trend will continue with our advancements in technologies and user requirements. One of the big portions of the world’s overall data transmission and data storage is our Videos and Images. Security and surveillance, entertainment, streaming, and roughly every other industry use this kind of data for their applications and the demand for data is increasing than ever. But this increasing demand for data causes two major (global) issues: first, during transmission, they can take a lot of bandwidth of our network, and second that they tend to take a lot of storage space since we need a lot of data points to effectively utilize them for our needs.
Here, this project will be showing the downscaling and upscaling algorithms that are already used in many applications for quite a few years and implementing these algorithms on FPGA and cloud effectively to get the best possible results. Initially, data can be taken from a low-resolution input(or can be downscaled) and then transmitted/stored. When we have to use it, upscaling can be done. These algorithms show very promising results while using fewer resources as to if directly high-resolution input be used from the beginning.
This will give us more bandwidth and storage to work with for our applications, and as computation will be done on FPGA, it will be easily scalable. Edge computing like this will effectively increase productivity and will help in a sustainable advancement in technology. For the continuous advancement in technology and sustainable growth, we have to use our resources efficiently and intelligently and I hope that this project can play a small part in this.
Health
FPGA based Covid-19 detection using Lung Ultrasound Image
AP037 »
With the onset of the Covid-19 pandemic, there has been a tremendous impact on the lives of people globally. The global tally of the no. of infected cases is 229,293,200 and the total death toll is 4,705,498 as of September 20, 2021, and this is just the no. of accounted cases. Apart from this, the covid-19 genome sequence is continuously mutating which resulted in the generation of different and more dangerous types of variants like the delta and delta plus to name a few. The globe witnessed the horrific scenes caused due to the shortage of resources in terms of healthcare during the unprecedented first and second waves. The leading scientists have already predicted the onset of the third wave which is expected to start in the last quarter of the year 2021.
To tackle the third wave, the governments have started the vaccination campaign for the people. But still, as per the earlier predictions the third wave is inevitable and the third world countries that are lagging in terms of medical infrastructure would be affected the most in the oncoming third wave. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) is considered as the standard reference for the Covid-19 based testing but it has certain disadvantages like higher testing costs and longer processing time for the collected samples. Considering the factors like lack of essential infrastructure required for the testing and the capital required, we are hereby proposing a novel approach as a preparatory measure for detecting the presence of Covid-19 using Lung Ultrasound Imaging which in turn can be further deployed on a real-time basis with the help of Intel FPGA Cloud Connectivity Kit and Azure IoT Suite.
Compared to CT scans and X-Ray based detections, Ultrasound Imaging is low cost and radiation-free detection method. In this proposed approach, we would conduct a thorough literature review on the existing deep learning models which has been developed for predicting the covid-19. Based on the earlier approaches, a new model would be proposed which will be extensively trained with available datasets for addressing the limitations offered by the earlier models. Upon the satisfactory performance of the model in terms of accuracy, precision, and computation time, it would be deployed onto the FPGA Cloud Connectivity kit for real-time application. With the help of Azure IoT support, the Ultrasound Images from different centers can be obtained and the test results can be again diverted back to the respective centers at a significantly less amount of time as compared to the RT-PCR test.
This proposed approach will help set up a nationwide/worldwide low-cost testing facility with a significantly less amount of capital being invested. With this approach, we are intending to address the two major challenges prevailing in the present scenario with the first one being high testing costs and improved timing for generating the test results. This approach would in turn be helpful to combat the oncoming third wave of this Covid-19 global pandemic.
Food Related
Smart and IoT Solutions for Agriculture and Farming
AP038 »
An automated & central system to maintain following Organic product qualifications set by EU Council Regulation (EC) No 834/2007 & COMMISSION REGULATION (EC) No 889/2008
1. Respects nature's systems and cycles and sustains and enhances the health of soil, water, plants and animals and the balance between them
2. Makes responsible use of energy and the natural resources, such as water, soil, organic matter and air
3. Aim at producing products of high quality
4. Aim at producing a wide variety of foods and other agricultural products that respond to consumers’ demand for goods produced by the use of processes that do not harm the environment, human health, plant health or animal health and welfare.
5. The maintenance and enhancement of soil life and natural soil fertility, soil stability and soil biodiversity preventing and combating soil compaction and soil erosion, and the nourishing of plants primarily through the soil ecosystem
6. The maintenance of plant health by preventative measures, such as the choice of appropriate species and varieties resistant to pests and diseases, appropriate crop rotations, mechanical and physical methods and the protection of natural enemies of pests
Smart City
Project
AP039 »
hello
Other: Agriculture
Smart Farming Stick
AP040 »
Agriculture plays a vital role in Indian economy.India ranks second worldwide in farm outputs.Though crops are facing problem like pests, climate change, soil erosion, diseases water scarcity and this led to a great loss.Farmers who are able to diagnose these diseases are able to take actions on it.But for farmers who are not able to identity take improper actions.This destroys all the crops.At last we see there is huge loss of time, money and labour. Analysing the problem which farmers have been facing of years, we needed to come up with solution in which human interaction is minimal.Smart farming have already made its place in the society, to add to that we have come up with this improvised smart farming technique.Smart Farming Stick (SFS) by using these techniques our system will work as a guide, to assist the farmers by giving information.Farming is about risk calculation – But what if the risk can be calculated and cured beforehand.Analysis can help you with identifying the weakness and strength of the soil, resulting in more revenue generation and saving ample amount of time. Automated solutions and technology offer greater accuracy based on more efficient data collection and monitoring.