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The smart wheelchair developed for people with inabilities dependent on the eye-tracking and by utilizing the voice assistant module. The smart wheelchair contains two modules, including a module for processing the image, a wheelchair-controlled voice associate module and constrained by appliances. The module for picture processing comprises a camera mounted on the wheelchair that can capture the picture and handling those images. The captured picture moved into a Raspberry Pie micro controller process using Open CV to get pupil movement in the 2D bearing. The movement of pupil is then moved remotely to the module for managing a wheelchair. The eyeball movement is also used as the controller to regulate the operations. Speech recognition technology is a technology that provides a way of interaction for human with the wheel chair. Hence, the problems faced by the people can be easily solved by using this technology for controlling the wheel chair. This can be implemented by using the smart phone or smart assistant enabled device as an interface between the human and the wheel chair.

One of the limiting factors of performance of any communication system is bandwidth. In telephone systems, the operational voice frequency ranges from 300 to 3400 Hz and is called Narrow Band (NB). This NB causes remarkable depreciation of speech in terms of quality and intelligibility, specifically for elderly persons. Speech Bandwidth Extension (SBE) technique is used to increase the quality and intelligibility of NB signal. In SBE method, additional data about the lost speech frequency components is transmitted along with NB signal. A better-quality Wide Band (WB) signal is reconstructed at the receiver end using the transmitted missing speech frequency components. This paper explores the ability of SBE to enhance the quality and intelligibility of NB signal for elderly persons. The enhancement in the quality and intelligibility of NB speech for elderly persons is reasserted by subjective listening and objective tests.

In this paper the optimization of the design of a tunable coplanar patch antenna and results thereof are presented and discussed. The design optimizations resulted in a coplanar patch antenna that could be tuned over a range of 240 MHz (1.79-2.03 GHz) for a minimum return loss of 10 dB. The antenna has an Omni-directional radiation pattern and the gain is nearly constant over the tuning range with an average value of 2.2dB.

Traffic engineering (TE) is one of the effective methods of IP routing used in Service provider networks when routers are overloaded due to uneven utilization of links. Multiprotocol Label Switching (MPLS) is a routing technique used in computer networks that guides data packets from one node to other node based on the concept of short path labels and speeding the traffic flows to support multiple customers. This project describes the design and Implementation of MPLS VPN (Virtual Private Network) along with dedicated traffic tunneling known as MPLS-TE with the help of Resource Reservation Protocol (RSVP), Open Shortest Path First protocol (OSPF) and Border gateway protocol (BGP) for IPv6 customers. The network is designed and simulated in GNS3 platform with Wireshark and various QoS performance metrics of the network are calculated to analyze the operational behavior of the network. A performance comparison of tunnel enabled and disabled MPLS VPN network is executed as an additional objective.

As the Indian solar PV market is burgeoning with 100GW target by 2030, solar modules competition is fast increasing. On the other hand, the reliability of solar modules is critical and they are either degrading faster or failing catastrophically well before their expected lifespan. The developers with large solar power plants are at risk. It is prudent to deploy modules from 3 to 4 solar companies to mitigate such risks. A case study is discussed to find out the nature and root-cause of failures and exercising early detection of the supplier of non-performing solar modules.

A novel planar ultra-wideband (UWB) biconical antenna is presented in this paper. The antenna design has been optimized for best performance in the range 3.1 to 10.6 GHz. The antenna has an omni-directional radiation pattern. The antenna has been manufactured and tested. It has a low profile and a small form factor. This antenna is suitable for use in wireless applications such as: UWB systems, sub-6 GHz 5G systems, and wearable wireless devices.

In this paper, the design and analysis of a novel electronically tunable aperture-coupled microstrip patch antenna are presented. The design procedures are illustrated with the help of an example. The measured tuning range of the antenna is 875 MHz (1.395-2.27GHz) for a minimum return loss of 10dB. The paper includes, for the first time, detailed design guidelines as well as important results and insights from simulations and measurements.

Weather Monitoring, surveillance of enemy vehicles, sensed data delivery are few of the applications of Wireless Sensor Networks. All the applications want the nodes to spend their energy in the critical activities. Lifetime depends on the residual energy of the nodes in the network. In this work we modify the Global Energy Balance [1] algorithms to have better network lifetime by making use of fixed relay nodes at various positions in the network. The selection of relay node is based on the distance and residual energy of the relay node all through the route discovery practice. The FRNS scheme is compared with existing algorithms for diverse parameters like End to End Delay, Overall Hops Count, Overall Alive nodes and Dead nodes, Residual energy, Lifetime ratio, Energy Consumption, Throughput and Routing Overhead.

We develop a spiking neural network (SNN) based implementation of a feature based on melodic interval prevalence for composer classification of a musical composition. The network has an adaptive spike-time based weight update rule which accurately captures the classification feature. Compared to the non-neural network based baseline implementation, the SNN implementation has a performance of 95.4%. When the songs are corrupted by gaussian additive noise, the relative degradation in performance of our algorithm is lesser than what is observed in the baseline algorithm.We also demonstrate that the performance degradation of our algorithm is minimal over a wide range of perturbations in the internal parameters of our circuit, demonstrating the power of adaptive SNNs to perform complex discrimination tasks in a fault-tolerant manner.