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Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being integrated into situational awareness systems. These technologies enhance the ability to analyze large datasets, predict potential threats, and provide actionable insights in real time, thereby improving decision-making processes and operational efficiency. As situational awareness systems become increasingly interconnected and reliant on digital technologies, cybersecurity is becoming a critical concern. There is a growing emphasis on securing these systems against cyber threats and vulnerabilities, ensuring the integrity and reliability of situational data.
Organizations are seeking situational awareness solutions that can be customized to fit their specific operational needs and easily integrated with existing systems and technologies. This trend is spurring the development of modular & interoperable solutions that can adapt to a wide range of applications and environments. While traditionally associated with military and public safety applications, situational awareness technologies are expanding into non-traditional sectors such as healthcare, manufacturing, transportation, and urban planning. This diversification is attributed to the universal need for enhanced operational visibility and control.