Water Related
Static Water Bodies Monitoring system
AP129 »
With the present scenario of the world , water conservation and management is the one of the, if not the prime most, main concern. Especially in metropolitan cities like Bengaluru and its periphery, where water has depleted to almost to 300m below the water table. To rejuvenate it , the government has taken initiative of treating domestic waste water from Bengaluru to the districts of Kolar and Chikkballapur and their 40 lakes which were affected severely due to the drought previously.
The lakes are mostly situated beside farms which are over loaded with fertilizers because of misinformation of fertilizers and pesticides usage in farms. Its not easy to control run off from non-point sources like farms to the water bodies which leads to nutrients and minerals enrichment, further to eutrophication and decrement in dissolved oxygen level and imbalance in pH level, resulting in biodiversity loss and degradation of water body.
To overcome these problems, all the water bodies should be monitored on a regular basis and on the basis of data collected, authorities will make proper plan in development and rejuvenation of these water bodies and the biodiversity of this region consisting of all the lakes and farms, farmers who have farms along with these water bodies can also be encouraged to adopt for organic farming and reduce the fertilizer usage in farming.
From our Project, we will monitor the water quality, dissolved oxygen, pH level and also harmful gases that results from decomposition of organic matter,which will come of water surface which will result in green house effect and in turn global warming, and it will also provide us BOD(Biological Oxygen Demand) level of the water.
The data collected will be processed through FPGA and uploaded to cloud through iot node or long range modem to be analyzed by Government authorities and to act upon it.
Smart City
Smart Sewage System
AP130 »
The world’s urban population continues to increase.The City has to provide basic urban services like proper sewage system for an increasing number of inhabitants inrespecting both sustainable development and safety requirements. This challenge requires the construction of efficient urban sewage system ,that use latest technology, in particular the smart technology. Through smart monitoring as well as data collection and analysis, the smart technology allows a real-time supervision of smart sewage system. Analysis of both historical and real-time problems in sewage system helps in improvement in their management. Since the smart sewage technology is recent, its implementation suffers from a lack of field feed-back. The construction of large scale demonstrators ofsmart urban infrastructures is then necessary for a good understanding of issues related to this technology such as smart sensors, data storage, analysis and visualization, engineering exploitation, interaction with end users.
Health
FPGA Enabled Myoelectric Interface for Human Computer Interfacing
AP131 »
The aim of this project is to enable Human Computer Interfacing via a myoelectric interface. High speed signal processing paired with the non-invasiveness of myoelectric sensors would result in a stable yet safe method of acquiring relevant data from the human body and using it as a simple HID input. The FPGA would read analog data, amplify and filter it, and pass it through a neural network (trained for that particular person) to produce data that can be used by a client side program to simulate HID input similar to that of an analog joystick .This would help in making computers more accessible to both disabled people and people of age.
Water Related
Smart Rainwater Harvesting System
AP132 »
A smart, low power implementation of a rainwater harvesting system which would sense if it's raining or not and open the water tank lid automatically to conserve water. The idea is to implement the system in normal households in a budget friendly low cost manner to maximize water conservation. The system will consist of digital logic circuits to monitor the rainwater sensing equipment by using a FSM based design approach at regular intervals. The aim would be to design a compact system that would be easy to install on any kind of water tanks.
Smart City
ULTRASONIC BIRD DETERRING SYSTEM
AP134 »
The majority of birds under migration do so at night, when the atmosphere is cold and quiet, and they frequently find themselves deviating into cities due to their bright light. Birds are naturally drawn to light, according to scientists, therefore when they fly over a bright metropolis with tall structures at night, they are naturally drawn to it, unknowing that they are in perilous territory. This has a significant impact on avian diversity. In order to curb this complication, we opt for an ultrasonic based bird deterrent system using image processing and cloud technology. The Intel FPGA Cyclone controller was employed in our project. The reason for choosing FPGA Cyclone controller because of its low power consumption, high bandwidth performance, and inexpensive cost. Our target users are people who own sky-scrappers and ornithophiles(bird lovers).
Smart City
Word Level Sign Language Detector
AP136 »
Sign language is used by members of deaf community to communicate .Each hand gestures in the language corresponds to a meaning.
In India there are over 5-million deaf people but there are only 250 certified interpreters which is one Interpreter for every 20000 deaf-people .
It is a practically impossible to balance this ratio between Interpreters and Deaf people ,this is where our project comes into action.
We propose "Word Level Sign language Detector " for Indian Sign language by using INCLUDE Dataset which contains 2-3 second videos with the sign mentioned.
This can prove as a Game-Changer for deaf community people to interact with other people.
This detector device can be used in places like Information service centers in railway stations for deaf people to get interact and communicate with people and can get the required information with less effort.This device increases the inclusivity for the deaf people and makes them feel comfortable in public places.
First we are planning to extract key pose features points (body-positions ) and then we feed these videos in to Neural network architecture to find the spatial differences between the frames, with that we think we can build an model to classify the signs to words.
This Word Level Sign language Detector model is finally deployed in FPGA . A camera is connected in FPGA which is placed infront of the signer which captures the real time video of the sign and predicts the respective class of the sign.
Food Related
Smart Embedded System for Food authentication using NIR
AP137 »
Food authentication has become a well-recognized regarding issue in food markets as, nowadays, several customers have to be compelled to be assured spiritual authentication in their food decisions and additionally different protection against counterfeit practices in food industries. Food authentication validates label info regarding the food origin and production method. Food authentication may be a speedily growing field thanks to raising public awareness engross food quality and safety. This paper presents crucial the analytical techniques that square measure used for genuineness analysis, explaining however and why they furnish possible solutions. Classification of various technology relies on genuineness indicators providing insight into forthcoming developments. The planned paradigm system consists of 2 elements. the primary section is that the sensing and therefore the second is knowledge assortment. This extremely integrated device delivers a 6- channel multi-spectral sensing within the near-infrared wavelengths from roughly 610nm to 860nm with fullwidth half-max of 40nm
Smart City
SMART WASTE MANAGEMENT SYSTEM
AP138 »
The project is based on a waste management system, which helps in maintaining environmental hygiene. Overflowing dustbins has always been a problem to the environment. So for a smart lifestyle, cleanliness is needed, and cleanliness begins with the Garbage Bin. This project will help to eradicate or minimize the garbage disposal problem. This process is effectively carried out with the help of IOT, an advanced technology.
Water Related
BioCam
AP140 »
Design and build an underwater BioCam for monitoring aquatic life, utilizing DE10Nano
Health
Multimodal analysis of complete behaviour of elderly and differently-abled people
EM046 »
What problem: Our mental health is as important as our physical health. To evaluate a person's overall behaviour, especially for the elderly and the differently-abled people, it is necessary to accurately analyse both physical and mental behaviour. Through the various camera, inertial and location sensors, it is possible to build a complete model which is able to describe the overall behaviour of human beings with details including emotional, physical and environmental aspects. In this project, we aim to address this issue and try to solve it. Furthermore, we will incorporate the advantage of edge computing and build a near-sensor solution that can monitor the overall well being of an individual.
What and how: In this project, we approach solving the problem by designing an efficient Deep Neural Network architecture.
First, in order to perform emotion analysis and correctly classify various human emotions of sadness, happiness or anger, a Convolutional Neural Network (CNN) based model would be designed. Information from camera sensors would be fed into this CNN model, which would correctly classify human emotions.
Next, we would design a hybrid network that employs the advantages of spatially deep CNN and temporally deep Long Short Term Memory (LSTM). This hybrid CNN-LSTM network would be used for analysing various complex human activities including walking, sitting and lying down - all of which would be collected using inertial sensors attached to the human body.
Lastly, a final deep neural network (DNN) model would be designed, which would combine the processed information of an individual's emotional analysis and activity recognition. This NN model would be crucial to accurately analyse the overall well being of the individual, for example, whether the person is having a problem while walking or not. When an individual is found to be in any distress - physical or mental, the responsible caregiver would be alerted by a signal or a message sent to him/her.
Today, a majority of the DNNs are implemented on the cloud. This design will remove any drawbacks associated with communication links to the cloud and will use the benefits of edge computing. The concepts of stochastic computing (SC) will be used in order to reduce the hardware resource utilisation of the DNN implementation. SC also reduces the complexity of the individual operations of the neural networks. For example, a multiplier can be implemented by only an AND gate or an XNOR gate and an adder can be implemented by a MUX in SC. This significantly improves this implementation and makes it ideal for edge computing.
Today, a majority of the DNNs are implemented on the cloud. Our design will remove any drawbacks associated with communication links to the cloud and will use the benefits of edge computing.
According to our knowledge, there is no existing autonomous solution that can accurately monitor the overall well being of an individual in their daily lives. In our project, we will design a DNN model which can compute and analyse the information near the sensor and not depend on cloud computing. Our model will be extremely useful in monitoring the health of any individual - especially the elderly and the differently-abled. They would be under constant supervision even if the designated caregiver is not physically present right next to the individual.
The prebuilt face and object detection models will be used . We would use the smart camera and these prebuilt algorithms would help us to correctly analyse the emotions and locality of the individual under supervision. Another advantage of using the provided kit with the FPGA board is to be able to parallekize our CNN and hybrid CNN-LSTM models, as there is no data dependency between them. The video processing based emotion analysis can be done much faster compared to CPU or GPU implementations by using the concepts of pipelining. The SD card would be loaded with sensor signal data and these data would then be processed by the neural networks. The CNN model will be used to process the data from the camera sensor and analyse the video frames and detect people, their emotions and also their locality. The inertial sensor data will be fed to the CNN- LSTM model that will correctly analyse human activities. The final DNN would then use the already processed information and provide a complete description combination for our models to run faster and better.
Water Related
Irrigation Truth
AS048 »
We propose to develop a miniature and low power Soil Moisture Radar (SMR) designed to be mounted on either a land based farm tractor or a low flying airborne platform such as a drone. A GPS module will allow the system to construct soil moisture maps during normal daily farm operation. These maps will allow managers to view the field as a whole and to identify irrigation patterns that are not as easily recognized at ground level, reducing water use and allowing selective crop irrigation thereby reducing water consumption and increasing crop yield.
Food Related
FarmoDictor
AP141 »
Maintaining soil fertility is essential for the prosperity and sustainability of any agricultural system. With the rise in population and increase in food demand, soil fertility management is essential. Lack of resources and improper soil management was the main cause of the problem resulting in soil degradation and nutrient, hence a decrease in productivity.
Accordingly, the objective of the project will be, to estimate the soil fertility on a real-time basis and to give suggestions regarding the suitable crop to be grown on a particular land along with fertilizer and compost usage. This project will educate the farmers about the variety of crops that can be grown on the soil which can have several financial and environmental benefits.
The project will provide crop advisory to the farmers by taking various factors such as weather conditions, soil nutrients, moisture levels and land type into consideration. The whole system will consist of a Hardware Device, Cloud Database and a Mobile Application and a Website. The Hardware device will be integrated with Soil Nutrient Sensors that will detect the macronutrients such as Nitrogen, Phosphorous and Potassium along with Soil pH, through the principle of Electrical conductivity. The device will also record real-time soil moisture, atmospheric temperature and humidity levels, rainfall, wind and light intensities which will be fed to the Cloud for further analysis. Later on, the collected data will be analyzed in the Cloud and a list of suitable crops that could produce better yield will be provided along with the amount of fertilizer to be used according to the crop type. In the Mobile application, climatic conditions and other geographical features along with the detailed soil nutrient report will be displayed on a real-time basis. Farmers will also be notified to perform soil tests regularly over a particular period, and the required amount of fertilizer will be suggested. It will also connect the farmers to agricultural experts for providing support and improving their overall yield.
Through this project, we are trying to break the rice-wheat monocultural practices which in turn reduces the pressure on the water table as rice and wheat, which are among the most water-consuming crops. Also, as the farmers would get a better understanding of the type and amount of fertilisers that can be used in the soil, this could lead to a reduction in soil and groundwater pollution. Variation in cropping patterns can also increase the income of farmers and improve their financial condition. Lastly, as the buffer stocks are filled with a variety of crops, the prices of these crops will go down in the market and benefit the consumers as well.