HYBRID MILITARY POLICE INTELLIGENCE: INTEGRATION OF DIGITAL SYSTEMS, DRONES, AND RIVER OPERATIONS IN THE AMAZONAS MILITARY POLICE

Abstract

The Amazon region, which includes the state of Amazonas, is part of a complex territory that poses many challenges to Brazilian public security. This is because its vast geographical area, the predominance of river transport, and population dispersion hinder a permanent state presence. In this context, police intelligence is necessary to strategically compensate for the physical limitations of territorial control. In light of the Intelligence-Led Policing (ILP) paradigm and contemporary discussions on data governance and artificial intelligence, this article aims to analyze the informational limitations of police intelligence in a hydro-forest environment and propose a theoretical model of Information Architecture for Police Intelligence in Complex Territories, applicable to the Amazonian context. Methodologically, this is a qualitative, descriptive-analytical research study, based on a specialized national and international literature review, an institutional analysis of the Integrated Policing and Operations System (SIPOM), and a case study based on publicly available operations carried out in Amazonas. Based on the articulation between literature on experimental evaluation of ILP (Intelligence-Led Policing), technological integration in intelligence centers, and studies on environmental crimes in the Amazon, it is argued that the effectiveness of intelligence does not depend exclusively on technological incorporation, but on the consolidation of integrated data infrastructure, informational standardization, interoperability, and qualified analytical training. It is concluded that strengthening the state's informational capacity is a central element for the consolidation of strategic intelligence in the Amazon, requiring ethical governance, institutional maturity, and systemic integration as conditions for the efficient use of digital technologies and data-driven solutions.