Application of Machine learning in Energy, Health and Disaster management.
Performance evaluation and modeling of ANNs by training on iris data sets.
Evaluation of decision models on cancer symptoms and tumor data.
Optimizing ANNs or CGPANN for energy, infrastructure, data and computing, bio-medical engineering, production, stocks, disaster management and weather.*
Automatic seed cultivator with control system and green energy recharging.*
Creating Mining Pool for cryptocurrency mining and Linking with Specific CC. (Future PhDs/Simulation)*
Application of feedback tree based nodal network for web article preservation. (Future PhDs/Simulation)*
Wireless charging using Infrared beam. (R&D)
Design of multi-beam wireless charger. (R&D)
Design of self scanning single-beam/multi-beam wireless charging port/location. (R&D)
Indoor localization using ZigBee modules and IPv6. (Research/Simulation)*
Simulating Internet of things and performance evaluation of ZigBee based Modular IoT. (Research/Simulation)*
Small scale IoT for temperature, humidity and pressure sensing. (Research/Simulation)*
Learning trends in chaotic time series and developing forecasting models using Neural Networks. (Research/Simulation)
Wind Speed forecasting using Artificial Neural Network (ANN) and its comparison with state of the art forecasters. (Research/Simulation)
Load Balancing in Data centers using ANNs and Support Vector Machines (SVM). (Research/Simulation)*
Data resource allocation and parameter estimation using forecasting models in cloud Infrastructure. (Research/Simulation)*
Analysis of power and communication mechanism in capacitor based motes in smart dust. (Research/Simulation)*
Currency and Forex forecasting. (Research/Simulation)
Detecting trends from stocks' candle-stick patterns using templates. (Research/Simulation)
Daily candle-stick forecasting using ANN and its comparison with other forecasters. (Research/Simulation)
Cryptocurrency forecasting for short-term and long term time devised terrains, (Research/Simulation)
Extrapolation of Ichimako Cloud for forecasting future trends in stocks using forecasting techniques, (Research/Simulation)
Relative stock Index extrapolation using ANN, (Research/Simulation)
Magnetic Sensor based road vehicle detection. (R&D)
Magnetic sensor based vehicle speed calculation – interfacing with MCU. (R&D)
Magnetic Sensor based vehicle length estimation. (R&D)
Magnetic Sensor based congestion control in autonomous traffic - Intelligent Transportation System Advents. (R&D)
Analysis of Internet Traffic for application Layer in IoT
The role of the research is to analyze these protocols on real world hardware emulations using Contiki and Also simulating the protocols on NS3 for the comparison of real work vs simulated results. The work is preliminary of IoT application development, security, integration, scalability and constrained environment factors.
There are many application types that are run on IoT nodes. Based on IPv6 networking schemes, these applications are modified for different real world scenarios and are constrained. Data deprecated applications use REST,CoAP, MQTT, XMPP, DDS, Web Socket, etc.
CoAP enables edge devices and nodes to connect and share information with centralized systems using lower power.
MQTT focuses on onetime subscription or one session registration and then unidirectional data flow from the server side to its client(s).
MQTT focuses on onetime subscription or one session registration and then unidirectional data flow from the server side to its client(s).
Web Socket interface provides TCP based communication of IoT nodes with remote server both for data updates on the server and from the server.
DDS based applications are designed for tagging and Suppressed Due to Excessive Length assignment in Data and its secure or open access.
XMPP is relatively simple because it uses high level XML scripts. Though it is the most suitable protocol for heterogeneous IoT yet is has some drawbacks. Its commands are more specified and thus uses more CPU power for processing each command.