It is simply human to feel unsecure about something one can’t see and therefore doesn’t know. Achieving awareness is an integral desire, a hygiene factor. The end-state for knowing and being aware is to feel secure. And yes, though security is a mere notion, it’s also a goal.
In today’s world, the concept of security can be broadly categorised into two forms: personal security remaining the responsibility of an individual; and the delegated security, which is entrusted to external players. With the latter, we consider a multitude of means to provide security, but I take the state as the most prominent provider of delegated security as a focus for the coverage herein.
The security offered by states is segmented into altering categories, but always consistent of border security. Terms like border guarding, border policing, defending and protecting borders are all components of the same border security realm. Situational awareness (SA), and the continuous pursuit to its enhancement, is an intrinsic constituent of border security. The quality of SA defines the ability to design and perform operational tasks, but also the level of protection and the sense of security resulting.
The current state of border security is under immense strain. Systems and their provided data are fragmented, threats are more dispersed and complex than ever before, skilled personnel are in decline, and the public’s expectations are often beyond what current capabilities can deliver. Achieving a desired level of border security requires a dedicated contribution from all elements, but also a calculated balance between them, and dynamic means of compensation.
To address this imbalance is notably a complex task. It requires a fundamental shift in how security is achieved. The answer we are looking for lies in technology, specifically in smarter, more adaptive, and integrated systems that reduce reliance on human operators while enhancing performance. Modern systems must be able to monitor, detect, identify, assess, and predict situations with minimal human interference.
This is where modern technologies like machine learning, data analytics, even artificial intelligence, if you wish, become transformative. In an environment defined by complexity, unpredictability, and diminishing human resources, technology is expected to amplify capabilities, restore coherence, and enable foresight, and all for the qualitative increase of border security.
So, what will the new technology, or new tech bring?
It detects anomalies, recognises patterns, and forecasts threats with unmatched speed and scale. Whether flagging erratic vessel behaviour or pre-empting incursions, it enables the kind of pre-emptive action necessary in high-stakes scenarios.
As trained personnel become scarce, new tech helps shoulder the operational burden by automating routine tasks, reducing decision fatigue, and empowering humans to focus on context-driven challenges. This human-machine synergy is key to efficient and scalable border security.
New tech allows for real-time asset allocation, adjusting priorities based on live data and threat levels. Border patrols, drones and other mobile assets, and communication networks can be dynamically redirected, ensuring that resources are deployed where they’re needed most.
New tech learns. With continuous feedback loops, machine learning systems evolve alongside emerging threats, making the entire border security infrastructure not only responsive but resilient.
In this new tech paradigm, decision-making becomes fluid. No longer stuck at the top, but able to move seamlessly across levels of command. Thanks to improved data synthesis and delivery, operators at every level can make informed decisions tailored to their scope and context. This means that the centre of command can be shifted between the command levels and focus where it’s the most relevant.
Indeed, future sensors are expected not only to monitor and detect, but also to identify. System’s software to analyse, alert and task, enabling pre-emptive action rather than delayed, reactive responses. Behavioural analytics and predictive algorithms expected to play a key role, swiftly identifying patterns and forecasting next moves. Data analytics to become the multiplier in automated identification, alerting and tasking. Machines are expected to take over repetitive tasks, never tiring or losing focus. While not foolproof – they can still be deceived – machines will not fail the tasks they are assigned. Machine learning ensures that once deceived, a system learns, adapts, and is not fooled again, or at least not by the same move.
New technologies will enhance border surveillance sensors increasing their detection performance, and providing additional intelligence to identify objects and their potential doing. This will increase both, the performance of a single sensor, and the output of multitude of sensors in case of overlaying set-up. In practical terms, a swimmer will be detected from distance and identified as a swimmer, and a ship type X identified as ship type X with limited false positive and no false negative results.
The excel is foreseen also on sensor fusion aspect. Integrating solid inputs from radar, electro-optical systems, satellites, AIS, mobile assets, and communication intercepts, the system software can increase the distance and accuracy for object detection and identification. Furthermore, to transform the fragmented data into a single, unified operational picture, allowing relevant operational response.
Security is no longer just a matter of strength or presence, it is about awareness, speed, and adaptability. As borders become more complex and the risks more dynamic, the integration of novel technologies offers a path forward. It doesn’t replace the human element – it enhances it.