With the invention of IoT, the image processing is reaching upto a distinct level as IoT is becoming a major part of every one life. These systems are creating many applications in image processing field such as image filtering and processing. The realization of this system was completed by means of a low cost ZedBoard Zynq 7000 FPGA and a Raspberry-pi. The output for the input image after processing various image processing filters process viz. Gaussian filter, Sharpening filter and Average filter has been obtained and these results have been displayed on VGA monitor. Also The edge detection and grayscale operations have been performed for Lena's image having size of 256×256. Chip utilization has been noted.

In this paper, we investigate the non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (M-MIMO) techniques and through simulation, and a comparison is given between the NOMA and orthogonal multiple access techniques. Integrating NOMA with M-MIMO is a very challenging task. In this paper, for a single-cell system, NOMA is integrated with a M-MIMO system for better spectral and energy efficiency. Investigation of the multiple user gain is the focus of this work because the multiple user gain supports simultaneous transmission of multiple users in the case of the M-MIMO system. In this way, the M-MIMO will provide a 100 times channel capacity increase, which results in very high data transmission rate. In the modern communication system, achieving multiple user gain is a very difficult task when channel estimation error is present. The performance of the orthogonal multiple access as well as NOMA system significantly reduced in the presence of channel estimation error. However, most of the current schemes do not work well with imperfect perfect channel state information conditions. Simulation results closely agree with the theoretical outcomes.

Nowadays, The incorporation of different function of the network, as well as routing, administration, and security, is basic to the effective operation of a mobile circumstantial network these days, in MANET thought researchers manages the problems of QoS and security severally. Currently, each the aspects of security and QoS influence negatively on the general performance of the network once thought-about in isolation. In fact, it will influence the exceptionally operating of QoS and security algorithms and should influence the important and essential services needed within the MANET. Our paper outlines 2 accomplishments via; the accomplishment of security and accomplishment of quality. The direction towards achieving these accomplishments is to style and implement a protocol to suite answer for policy-based network administration, and methodologies for key administration and causing of IPsec in a very MANET.

ISFET area is a promising technology developed recently, with widespread application in ion based sensing applications such as PH measurement, TPS & water quality measurement & other ION sensitive chemical and biological measurements. To utilize ISFETs to form an integrated ph sensor is a promising avenue. To implement ISFET based ph sensors the need of calibration of V _th various / id variation of with per instance measurement of actual ph value is required. This waste introduces a unique concept of dynamic auto calibration of ISFET pH sensor, using reconfigurable FPGA hardware architecture in conjunction with artificial intelligence. The proposed work employs real time on the fly calibration system. Where in the output voltage of ISFET is sampled by ADC at various ph level & the same are digitized and sent to calibration pc/laptop, whereas in an artificial neural network learns the voltage output ph curve, & predicts the voltage values at various ph levels vs. Voltage output values & programs LUT (look up table) in FPGA flash. After calibration, the device captures ISFET Vout values from ADC and searches the lookup table, computes compensation value & feed DAC to compensate the voltage output of ph sensor as per tradition standards in real time.