Research Topic

Cognitive Autonomy in Robotics and IoT-Based Platforms for Surveillance Applications

About this Research Topic

Autonomy comprises a fundamental capacity for various systems at any level including surveillance-oriented frameworks. From early years, the topic gained significant attraction within the research community presenting pioneering solutions in a variety of applications, including surveillance. More specifically, surveillance and monitoring systems aim at facilitating the capacity of the corresponding personnel to a more accurate and efficient supervision of either limited or wider territories depending on the extension of the sensor network. First responders, security agencies etc., extensively utilise such solutions to increase their operational efficiency and moderate the impacts of hazardous events via early detection and identification of potential threats.

Considering the progress achieved in the artificial intelligence (AI) field during the last decade, improved AI models were also capitalised for optimal surveillance frameworks. Nonetheless, such autonomous systems still face diverse challenges that motivate the design and the development of novel approaches for improving the accuracy under real conditions. The use of cutting-edge sensory systems accompanied by novel capabilities such as object recognition could be rather beneficial for the surveillance domain aiming at early event identification and improvement of the operational autonomy allowing the corresponding personnel to focus on their actual operational needs and obligations. Most of the existing approaches focus on validation processes under ideal environmental conditions resulting in limited deployments.

The main goal for this Research topic would be to present pioneer solutions resulting from recent advancements that can outreach such restrictions and release the full potentiality of these approaches in this specific application area.

The main focus of the Research Topic will be to promote advancements and progress in machine cognition and more specifically for surveillance applications. The submitted papers are expected to cover wider operations and functionalities that will focus on delivering autonomous systems to assist monitoring personnel in hazardous situations and dangerous events.

Manuscripts should cover the use of a variety of IoT sensors but not limited to (e.g., drones, hand-held cameras etc.) while the deployed models should be validated under real operational conditions to maximize their impact, assess their applicability and estimate their performance for relevant systems. These include, but are not limited to:

• Sensor-based navigation for unmanned vehicles
• Programmatic control of UAVs and swarms
• Multi-robot systems for increased situational awareness
• Effective collaboration between heterogeneous systems
• End-to-end learning for robotics deployment
• Cobots in surveillance applications
• IoT networks for optimal area monitoring
• Enhanced cognition operations for surveillance systems
• Object detection for multimodal optronics
• Action recognition based on multimodal sensors
• Edge cognition in monitoring operations
• Drones and AI in disaster management support

Topic Editor Benny Mandler is a Research Staff Member at IBM. All other Topic Editors declare no competing interests with regard to the Research Topic subject.


Keywords: Robotics, Heterogenous systems, IoT-based processing, Embedded systems, Cognitive surveillance, Autonomous operations


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Autonomy comprises a fundamental capacity for various systems at any level including surveillance-oriented frameworks. From early years, the topic gained significant attraction within the research community presenting pioneering solutions in a variety of applications, including surveillance. More specifically, surveillance and monitoring systems aim at facilitating the capacity of the corresponding personnel to a more accurate and efficient supervision of either limited or wider territories depending on the extension of the sensor network. First responders, security agencies etc., extensively utilise such solutions to increase their operational efficiency and moderate the impacts of hazardous events via early detection and identification of potential threats.

Considering the progress achieved in the artificial intelligence (AI) field during the last decade, improved AI models were also capitalised for optimal surveillance frameworks. Nonetheless, such autonomous systems still face diverse challenges that motivate the design and the development of novel approaches for improving the accuracy under real conditions. The use of cutting-edge sensory systems accompanied by novel capabilities such as object recognition could be rather beneficial for the surveillance domain aiming at early event identification and improvement of the operational autonomy allowing the corresponding personnel to focus on their actual operational needs and obligations. Most of the existing approaches focus on validation processes under ideal environmental conditions resulting in limited deployments.

The main goal for this Research topic would be to present pioneer solutions resulting from recent advancements that can outreach such restrictions and release the full potentiality of these approaches in this specific application area.

The main focus of the Research Topic will be to promote advancements and progress in machine cognition and more specifically for surveillance applications. The submitted papers are expected to cover wider operations and functionalities that will focus on delivering autonomous systems to assist monitoring personnel in hazardous situations and dangerous events.

Manuscripts should cover the use of a variety of IoT sensors but not limited to (e.g., drones, hand-held cameras etc.) while the deployed models should be validated under real operational conditions to maximize their impact, assess their applicability and estimate their performance for relevant systems. These include, but are not limited to:

• Sensor-based navigation for unmanned vehicles
• Programmatic control of UAVs and swarms
• Multi-robot systems for increased situational awareness
• Effective collaboration between heterogeneous systems
• End-to-end learning for robotics deployment
• Cobots in surveillance applications
• IoT networks for optimal area monitoring
• Enhanced cognition operations for surveillance systems
• Object detection for multimodal optronics
• Action recognition based on multimodal sensors
• Edge cognition in monitoring operations
• Drones and AI in disaster management support

Topic Editor Benny Mandler is a Research Staff Member at IBM. All other Topic Editors declare no competing interests with regard to the Research Topic subject.


Keywords: Robotics, Heterogenous systems, IoT-based processing, Embedded systems, Cognitive surveillance, Autonomous operations


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

24 September 2021 Abstract
28 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

24 September 2021 Abstract
28 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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