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COVID-19 is a new strain of coronavirus that had affected nations at a global scale. With an unprecedented high infection and mortality rate, the World Health Organization had declared this novel virus as a pandemic phenomenon in March 2020. Due to the seriousness of this situation, efforts to control and surveillance of this emerging disease are currently of global interest. This chapter will focus on analytical performance of biosensor and artificial intelligent (AI) technologies for the development of robust sensor to detect COVID-19. The future outlooks of biosensor and AI to be employed remotely for COVID-19 detection and diagnosis will also be discussed.

This study reports a new method of fabrication and application of “green” starch nanoparticles (SNPs) from local sago (Metroxylon Sagu) starch granules employing a high-pressure homogenization procedure. This approach is environmentally friendly, highly feasible, low cost and chemical-free with large-scale production capacity. In this work, SNPs' morphological, particle size and thermal properties were studied. The effects of SNPs concentration (ranging from 0 to 8% w/w) as nano-fillers in composite films’ barrier, transparency and contact angle were also investigated. Our results have shown that the fabricated SNPs exhibited excellent uniformity and spherical shapes. Addition of SNPs have demonstrated to enhance polymeric structure of nanocomposite film due to decreased water vapour permeability and increased contact angle. Sago SNPs as fillers pose an excellent prospect in green composites fabrication for material and biomedical purposes with potential application as carriers for drug delivery.