There are many devices at homes, factories, hospitals, cars, and thousands of other places. With the proliferation of devices, we increasingly need solutions to connect them, and collect, store, and analyze device data. Connecting everything and everyone, IoT is making the world smarter and better than ever before. The Internet of things (IoT) is the extension of Internet connectivity into physical devices and everyday objects. IoT devices are implemented using both hardware and software components.
Dedicated hardware components are used to implement the interface with the physical world, and to perform tasks which are more computationally complex. Microcontrollers are used to execute software that interprets inputs and controls the system.
Traditional fields of embedded systems, wireless sensor networks, control systems and automation are fields enabling IoT. The definition of the Internet of things has evolved due to convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems. When it comes to developing embedded IoT devices, the hardware design is viewed as a critical component for the success of the IoT product.
Healthcare based applications
Water quality and quantity measurement system
FPGA based high computing (accelerators)
Radar based system using FPGA
Lab on a chip (VNA)
Cooley-tukey algorithm implemented on FPGA
Cloud based data communication
Smart home applications
We here, try to find end-to-end IoT solutions, which include design, develop, integrate, deploy and management of end to end IoT processes. This empowers smart industries, smart living and smart enterprises and deliver connected experiences by connecting assets, operations/logistics, and services. We focus predominantly on smart living – Wearables, Healthcare, Security. Enhance the quality of life by embracing emerging technologies designed to foster healthier, happier and safe environment.
A novel methodology that uses a combination of electrocardiogram (ECG) and photoplethysmographic (PPG) signals to estimate BP accurately.
Worldwide, deaths due to cardiovascular diseases are on the rise and a large proportion of them can be attributed either to hypertension or hypotension making blood pressure monitoring an important factor in disease prevention. However traditional methods of BP monitoring while aplenty, have many drawbacks. To combat these, we have developed a unique algorithm for cuff-less ambulatory BP recording that overcomes current limitations. Applications of IoT in the healthcare space are not new and its usage has only increased manifold transforming the landscape of real-time health monitoring. The most widely used methods of monitoring BP are intermittent and cuff-based. Not only does repeated tightening of the cuff around the arm cause tissue damage due to occlusion of the artery, but in the case of digital monitors, it is not entirely reliable and precise. To measure blood pressure accurately and to capture fluctuations, it is essential to measure it continuously during a specified period. This is especially true in the case of low BP or hypotension where prior symptoms may not be typically experienced but if left untreated may cause damage. However continuous devices are prohibitively expensive and typically used in the care of critically-ill patients.
We have been working on a novel methodology that uses a combination of electrocardiogram (ECG) and photoplethysmographic (PPG) signals. The device which is currently being prototyped is portable where the patient has an ECG electrode attached to the chest as well as a PPG light source sensor worn like a sleeve over a finger. Data is collected simultaneously by both these sensors using Arduino and BP is estimated using pulse wave transit time (PWTT). Using bluetooth, data is transmitted to a mobile phone where an application on the phone reveals the required waveforms. The same data can also be uploaded onto a server where it can be processed. Not only will the device score in its compact dimensions, it is proposed to consume less energy allowing it to have a prolonged battery life. With its ability to process data in-node, it will also save considerable bandwidth.
This research work related to the findings on affordable, robust and compact smart water
meter. As Peter Drucker said that “You can't manage what you can't measure." Hence, in
this work designing of a smart water meter is suggested for smart cities.
To design a smart water meter mainly three components are required flow sensor, processor and communication protocol. In this project, a smart water meter is designed using Wi-FI SoC and helical turbine flow sensor.
Work in Progress:
The mechanical flow sensors used in the designing of smart water meter has various flaws in it. To overcome the limitation, a cost effective non-invasive flow sensing technique is developed using ultrasonic transducers.
Gait characteristics have been linked with a variety of medical conditions in clinical research . Current methods for detection are too expensive, complicated, uneasy and require skilled personal for usage. We aim to utilize Guided-Path Tomography (GPF) to develop an inexpensive, easy to use mechanism for gait measurement. The goal is to reduce cost, while improving reliability, ruggedness, and accuracy. This project aims to recognize the medical condition from the analysis of gait measurement. Plastic Optical Fibers (POF) are proposed to be used as sensing element due to their higher sensitivity to bending compared to glass fibers and low cost.
The deformation-induced transmission losses through strategically placed optical fiber
sensing elements will be measured and images of the footprints of objects reconstructed
by an original method suitable for the datasets acquired. The proposed method offers
advantage as the POF elements introduce characteristics typical of a distributed sensor
and is particularly efficient for large areas.
Such a system can potentially be used to recognize people at risk of falling, identify diagnostic measures that are predictors of fall-prone elderly, detect subtle gait changes early so that effective interventions can be made in a timely manner to prevent or reduce severe health outcomes.
Gait recognition could lead to applications exploiting information of biometric character, such as asymmetry (limping), variability (Unsteadiness), compensatory strategies and adaptive gait. It can also be used to detect flat feet. A number of additional indicators of gait and balance related to medical conditions, such as the position of the body mass centre, joint mobility and plantar pressure can be extracted from the deformation. Capability to distinguish between the calcaneus and metatarsus bone can be used for more detailed analysis.
The research is related to design a On Chip Low Cost Vector Network Analyser for wide frequency band which will able to measure & display Reflection and Transmission coefficients.
VNA is a measurement device that is used to measure the S-Parameters of the RF and Communication device. Modern days research and academics require Vector Network Analyzers (VNAs) for analysing various communications devices.
But VNAs are very expensive and bulky because of which a lot of research does not happen. So, to solve this problem a Low-cost and portable two-port vector network analyzer (VNA) which will work for a wide band of frequency range will be developed for vector reflection and transmission coefficient measurement of the RF devices and graphical user interface (GUI) will be designed to show the results on a LCD screen/Laptop.
The objective of this work is to design a parameter specific portable device for water quality measurement that can function as a substitute for spectrophotometers.
This work presents a low-cost, robust and easy to use technique for measurement of bulk water property changes, specifically pH, total dissolved solids(TDS), and turbidity. The designed multi-wavelength sensing mechanism is capable of measuring the absorption of light emitted by three different LEDs after passing through water. The LED light source illuminates the water sample and the transmitted light is captured by a photodiode, which produces an electronic signal. This is used to calculate the amount of absorbed light.
Research include optimal detection of multiple threat radars and determine the location of the source of threat radar. It involves developing algorithms for estimation of Direction of arrival of the incoming signals, frequency of the radar source and other various pulse parameters for passive wide band radar sensor. The research work also includes in developing an efficient algorithm for tracking the threat radars in a 100Km radius.The work also includes synthesis and simulation of algorithms on various signal processing hardware such as FPGA.