Other: Renewable energy applications
IoT oriented Battery Management System (BMS) for real-time and accurate Battery State and Health Monitoring targeting renewable energy applications
AP133 »
A Robust Battery Management System (BMS) for real-time and accurate Battery State and Health Monitoring is the most critical subsystem of any application which uses Battery Energy Storage Systems (BESS). The accurate monitoring of battery parameters is important to prevent any unforeseen catastrophic situation. We have proposed state-of-the-art Battery monitoring algorithms for estimating the State-of-Charge, State-of-Health, State-of-Power, and State-of-Function of Li-Ion Batteries.
The BMS algorithms will be developed on Intel FPGA and include functionalities such as overcharge, undercharge, and overcurrent protection circuits as well as Automatic cell balancing and uploading the data to the cloud. Such a novel design provides a power-efficient as well as a high-speed solution for the highly complex BMS.
Water Related
Monitoring and Predicting Urban Water Reservoirs
AP135 »
Water scarcity is a global crisis which is faced by many countries across the world. It is one of the most serious risk faced by the world at different sector(social, economic, political and environmental). Around 1.2 billion people, or almost one-fifth of the world's population, live in areas of water scarcity, and 500 million people are approaching this situation. Another 1.6 billion people, or almost one quarter of the world's population, face economic water shortage (where countries lack the necessary infrastructure to take water from rivers and aquifers).
Health
Smart Health Care Monitoring Unit for Bed Ridden Patients
AP139 »
A comfortable health monitoring unit which is wearable for
patients is presented .The unit is based on a wearable interface
implemented by temperature sensor, pulse detector, ammonia gas
sensor and accelerometer.
This unit works with existing devices including above mentioned
sensors. They are attached to patients cloth that transmits data in
wireless medium to central monitor.
To continuously monitor the health care aspects such as body
temperature, odour of NH3 gas , activity movement and location
of bed ridden patients.
Other: Educational
Logisim 2.0
AP011 »
Digital circuits design methods are considered as a fundamental knowledge base in Informatics, Engineering and Computer Science related study programs. This is because digital circuits constitute the basis of all the digital systems used these days. Knowledge of digital circuits is a basic requirement for the successful study and implementation of the complex technologies and systems, which are built around them. In courses devoted to the design of digital circuits, it is important that students are provided with the capability of verifying their designs with the corresponding experiments. This is particularly useful in teaching introductory engineering courses because the use of hands-on labs in the early years of the study suffers from restricted laboratory capacity and requires student training on the use of laboratory equipment and now due to this covid-19 pandemic it is not possible to visit physical library. Based on the above, the use of educational software tool Logisim together with cloud support provides significant advantages for the teaching of digital circuits, design concepts and computer architecture.
Data Management
Build SMTP relay with email scanner capability
AP001 »
SMTP can handle single or multi connection email sending request. SMTP relay fill forward to destination of email sender. Some attachment can put on email and require to scan before sending to public network. this a may have some unwanted files or executable that may danger to everyone recieved this email. this attachment may have some compressed file that may to extract and check before sending. This file probably may have DRM it before send
Transportation
Smart Driving Assistance
AP002 »
Using OBD-II port of vehicles to fetch data from the vehicles and monitor different parameters relating to emission, forecast engine failures & recommend good driving practices to conserve fuel.
Water Related
sustainable fishing
AP005 »
Our project is coming up with the cutting edge End-to-End product which can help the marine species and over a 5-10 years course wild capture would be rejuvenated naturally with the ultimate solution what we offer with the existing Hardware/Software but integrating and applying it for a unique way.
Smart City
(Panotti's Ears) Real time Voice Analytics Co-processor
AP007 »
Speech recognition models have been used extensively on various platforms to provide ease of use, digital smart assistance, and hands-free control. At the cutting edge of this technology, the use of hidden Markov models is common. To improve the computational efficiency of hidden Markov model-based speech recognition systems, various techniques are used, amongst which the Viterbi beam search algorithm is one of the best. However, for large vocabulary speech recognition models with larger beam widths, the beam search algorithm’s sparse matrix operations create a highly constrictive bottleneck. Traditionally GPUs have been used to accelerate such models but with the algorithm's not so parallel nature, GPUs don’t provide an efficient solution and power constraints of IOT devices completely rule them out for Edge level.In this project, we research and formulate an FPGA based Co-processor (RTL level abstraction) to accelerate sparse matrix operation of the beam search algorithm so it can be used on edge devices to revolutionize how we interact with IOT edge level devices.
Industrial
FPGA based Wireless Sensor Networks
AP009 »
Wireless Sensor Networks (WSN) implementation on FPGA connecting multiple nodes with different sensors from analog devices and actuators to make industrial work more independent of human control physically. The data management will be made possible using Microsoft Azure cloud services, making the data accessible as and when required to the controller and the specifications can be tuned at admin end. This project is to make cloud based applications on FPGA and to explore new emerging technologies to make them system independent using FPGA.
Smart City
Model-Predictive-Traffic-Mangement
AP010 »
We are proposing to build a hardware platform that's able to identify individual vehicles in real-time. The device will be connected to a real-time traffic model that's run on the cloud. Then by placing this device at a strategic location in a city, over time, we would be able to build a very accurate predictive traffic model.
Overall, we expect our project (hardware platform together with the back-end cloud-based software) will provide much better tools for city authorities to manage traffic than what's available today.
Transportation
AI based data-driven approach and hardware accelerators (FPGA) to predict the SoC, SoH and RuL of the LiBs
AP012 »
The advancement in digitalization and availability of reliable sources of information that provide credible data, Artificial Intelligence (AI) has emerged to solve complex computational real-life problems which was challenging earlier. However, Artificial Neural Networks(ANN) need rigorous main processors and high memory bandwidth, and hence cannot provide expected levels of performance. As a result, hardware accelerators such as Graphic Processing Units (GPUs), Field Programmable Gate Arrays (FPGAs), and Application Specific Integrated Circuits (ASICs) have been used for improving overall performance of AI based applications. FPGAs are widely used for AI implementation as FPGAs have features like high-speed acceleration, low power consumption which cannot be done using central processors and GPUs. In Electric-powered vehicles (E-Mobility), Battery Management Systems (BMS) perform different operations for better use of energy stored in lithium-ion batteries (LiBs). The LiBs are a non-linear electrochemical system which is very complex and time-variant in nature. Because of this nature, estimation of States like State of Health (SoH) and Remaining Useful Life (RuL) is very difficult. The goal is to develop an advanced AI based BMS that can precisely indicate the LiBs states which will be useful in E-Mobility. This gives useful information for the prediction of when the battery should be removed or replaced and helps to optimize the battery performance and extend battery lifespan.
Autonomous Vehicles
FPGA Implementation of Multi-beam Beamformer and RaDaR Processor for Highway Pothole Detection and Avoidance
AP015 »
Automotive RaDaRs that incorporate ADAS-AD perform a wide spectrum of monitoring tasks for event-free autonomous navigation. Most such systems are pulsed RaDaRs, because this principle provides high dynamic gain, short measurement times and unproblematic signal processing. On a subjective level, such ADAS application demands an antenna radiation pattern tailor-made for its efficient functionality. Having electronic beam steering capabilities with good resolution and imaging properties, in addition to satisfying the radiation pattern morphologies and peak side lobe levels, would give more functionality to existing ADAS applications.
Potholes on interstate highways and local roads have been a bane of road transportation worldwide. The presence of potholes has a devastating impact on the vehicular platforms – with the attended fiscal element – in addition to hampering a smooth and predictable flow of traffic that is paramount to future autonomous road transportation. The impact on air quality and driveability, on account of the sluggish traffic flow over a stretch of such degraded tarmac generating harmful vehicular exhaust from the laboured performance by its engines, is substantial.
A medium range RaDaR (MRR) would serve as a capable ADAS tool in this context. An MRR sets a requirement for availability of multiple instances of narrower beams that shall enable tandem detection of as many potholes over a particular stretch of degraded tarmac. An added functionality in this operation is the processing of RaDaR 2-D data in real time. The high spatial resolution radio image data would offer a measure of the pothole parameters, against which the autonomous driving aspect could be altered by a suitable proportion in the interest of defining the traffic predictability criterion. Such operations are highly computation-intense, with the need for agile engines to be implemented in hardware and software. The inherent parallelism and reconfigurability features offered by FPGAs would ably assist by providing an opportunity to specialize the data processing implementation as needed. This opportunity is likely to grow as the logic capacity of FPGAs increases and the cost of FPGA devices is reduced. In the aforementioned context, FPGA-based beamforming and radar processing systems would be developed, tested. and deployed. The RaDaR would be designed as capable of deploying upto 10 highly-directive beams that could enable sensing over a range of 50 m, with a range resolution of few tens of cm and a spatial resolution of few cm, without the aid of external delay elements. The use of FPGAs in vehicular radar systems and an analysis of their robustness would be comprehensively evaluated during the project.
An added element in the work shall be the geo-tagging aspect, that would help generate a vast database of all such pothole detections across a span of geography criss-crossed by all types of roads. A low-latency communication infrastructure would be paramount to this operation, given the pervasive access requirements placed on the data by multitudes of vehicular systems before they encounter any pothole from the catalogue. The database requirements could be met if they are cloud-based systems, that feature elements of data and system security.