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Natural reserves, such as the Santurbán Moor in Colombia, are ecologically important but face significant threats from activities like mining and agriculture. Preserving biodiversity in these ecosystems is essential for maintaining ecological balance and promoting sustainable tourism practices. Identifying plant species in these reserves accurately is challenging due to environmental variability and species similarities, complicating conservation efforts and educational tourism promotion. This study aims to create and assess a mobile application based on deep learning, called FloraBan, to autonomously identify plant species in natural reserves, enhancing biodiversity conservation and encouraging sustainable and educational tourism practices. The application employs the EfficientNet Lite4 model, trained on a comprehensive dataset of plant images taken in various field conditions. Designed to work offline, the application is particularly useful in remote areas. The model evaluation revealed an accuracy exceeding 90% in classifying plant images. FloraBan was effective under various lighting conditions and complex backgrounds, offering detailed information about each species, including scientific name, family, and conservation status. The ability to function without internet connectivity is a significant benefit, especially in isolated regions like natural reserves. FloraBan represents a notable improvement in the field of automated plant identification, supporting botanical research and efforts to preserve biodiversity in the Santurbán Moor. Additionally, it encourages educational and responsible tourism practices, which align with sustainability goals, providing a useful tool for both tourists and conservationists.

Currently, 4.0 technologies have generated important changes in government entities, promoting digital government transformation (DGT). This article addresses the challenge of improving the security, reliability and traceability of communications and certified notifications of state entities, particularly in the case of the Colombian government entity called the Comisión de Regulación de Comunicaciones (CRC). Four important points are presented in this report: (a) Research interest in blockchain and smart contracts has been greatly increasing, evidenced in a literature review conducted in the SCOPUS index; (b) a global reference framework on the use of emerging technologies, as is the case of blockchain, has been developed, as well as the legal and juridical framework in Colombia as a baseline; (c) a multi-criteria decision making framework has been used, resulting in the choice of the Zilliqa platform; and (d) The Tecnotifica™ V1.0 software tool is developed to automate notifications with stakeholders using blockchain. Its effectiveness and acceptance is validated with a technology acceptance level test (TAM). It is concluded that the incorporation of emerging technologies such as blockchain is of a very high interest and relevance in the digital transformation of the state sector in the world.