Deploying Computational Intelligence AI and Psychovisual Quality Optimization Tools in Embedded Image Coding to Enhance the MIoT PAYLOAD Features

Currently, the majority of the information and data that we are led to use are digitalized in order to transmit them in the computer networks, facilitate and accelerate their treatments and uses. This enthusiasm for the use of technology is hindered by several problems such as data storage, limited memory capacity, execution time, where we opt to work on the optimization of data when sending it with security rather than investing in infrastructure by increasing the storage and telecommunications capacity. Most of data are images emanating from several areas such as agriculture, industry or medicine, the latter which is in high demand given the increase in population growth and the spread of epidemics. This article proposes an IoT medical platform composed by IoT nodes containing photo cameras, image sensors such as MRI and/or scanners such as mammography, Doppler and other types of image sensors and readers of Barcodes and QR Codes, associated with identification readers, which are found in identity cards such as the national identity card, the health card of the patients, the passport or permit. The Barcode or QR Code is the unique identifier of the citizen and is linked to medical servers in national and regional health structures containing his health status. To optimize the payload to overcome the problems related to storage, execution time, memory and bandwidth, we will decompose, encode and encrypt the images before they are sent and when they are received we do the reverse process, namely, decrypting, decoding and reconstructing. And to do this, we will use a psychovisual quality based encoding using the properties quality criteria of the human visual system (SVH) for the processing of Barcodes and QR Codes, the foveal encoding for the processing the CoaP protocol payload within IoT platform, and ECC encryption protocol to secure these sendings during their communication.