Global plastic waste is increasing rapidly. In general, densely populated regions generate tons of plastic waste daily, which is sometimes disposed of on land or diverged to sea. Most of the plastics created in the form of waste have complex degradation behavior and are non-biodegradable by nature. These remain intact in the environment for a long time span and potentially originate complications within terrestrial and marine life ecosystems. The strategic management of plastic waste and recycling can preserve environmental species and associated costs. The key contribution in this work focuses on ongoing efforts to utilize plastic waste by introducing blockchain during plastic waste recycling. It is proposed that the efficiency of plastic recycling can be improved enormously by using the blockchain phenomenon. Automation for the segregation and collection of plastic waste can effectively establish a globally recognizable tool using blockchain-based applications. Collection and sorting of plastic recycling are feasible by keeping track of plastic with unique codes or digital badges throughout the supply chain. This approach can support a collaborative digital consortium for efficient plastic waste management, which can bring together multiple stakeholders, plastic manufacturers, government entities, retailers, suppliers, waste collectors, and recyclers.

This contribution applies tools from the information theory and soft computing (SC) paradigms to the embedding and extraction of watermarks in aerial remote sensing (RS) images to protect copyright. By the time 5G came along, Internet usage had already grown exponentially. Regarding copyright protection, the most important responsibility of the digital image watermarking (DIW) approach is to provide authentication and security for digital content. In this paper, our main goal is to provide authentication and security to aerial RS images transmitted over the Internet by the proposal of a hybrid approach using both the redundant discrete wavelet transform (RDWT) and the singular value decomposition (SVD) schemes for DIW. Specifically, SC is adopted in this work for the numerical optimization of critical parameters. Moreover, 1-level RDWT and SVD are applied on digital cover image and singular matrices of LH and HL sub-bands are selected for watermark embedding. Further selected singular matrices $S_{LH}$ and $S_{HL}$ are split into $3\times 3$ non-overlapping blocks, and diagonal positions are used for watermark embedding. Three-level symmetric encryption with low computational cost is used to ensure higher watermark security. A hybrid grasshopper–BAT (G-BAT) SC-based optimization algorithm is also proposed in order to achieve high quality DIW outcomes, and a broad comparison against other methods in the state-of-the-art is provided. The experimental results have demonstrated that our proposal provides high levels of imperceptibility, robustness, embedding capacity and security when dealing with DIW of aerial RS images, even higher than the state-of-the-art methods.