Case-based reasoning approach applied to surveillance system using an autonomous unmanned aerial vehicle

Pinto, Milena F.; Melo, Aurélio G.; Marcato, André L. M.; Urdiales, Cristina

doi:10.1109/isie.2017.8001437

Cited by 23 publications

(24 citation statements)

References 10 publications

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“…The general concept of the decentralized surveillance architecture was already discussed in [17]. Figure 1 illustrates the simplified diagram of the system.…”

Section: Proposed Cognitive Systemmentioning

confidence: 99%

“…In previous work, the Deterministic Finite Automata (DFA) was applied to fulfill this task due to its predictability, performance, and flexibility [17]. However, the DFA has a relevant limitation, that is, the inability to process the low-level numerical information along with the acceptance states, such as the likelihood associated in each recognized instance, which can be an essential factor to the higher-level decision-maker.…”

Section: Middle-levelmentioning

confidence: 99%

See 1 more Smart Citation

Aerial Human Activity Recognition Through a Cognitive Architecture and a New Automata Proposal

Pinto¹,

Melo²,

Marcato³

et al. 2020

Learn. Nonlin. Mod.

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Video surveillance often involves several actors in multiple interactions and modelling complex activities becomes a challenge, especially in real environments. When applying autonomous video surveillance, object recognition techniques are used to produce symbolic information related to the information present in a scene. An automaton is a specialized structure capable of accepting or rejecting those symbols producing an efficient computation structure for these types of data processing. This research work presents an innovative structure for the well-known Weighted Automata to organize the information from sensors, grouping these measurements into a symbolic representation of actions that are happening in the real world. This work also proposes a hierarchical architecture formed by a multilevel sensorial system comprised of low, middle and high levels to perceive the environment and to comprehend scenes. The proposed architecture is designed to operate in a decentralized way and onboard of the Unmanned Aerial Vehicles (UAVs). The experiments showed that this system updated effectively the semantic structure given the sequence of information and demonstrated the automaton and architecture effectiveness..

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“…The general concept of the decentralized surveillance architecture was already discussed in [17]. Figure 1 illustrates the simplified diagram of the system.…”

Section: Proposed Cognitive Systemmentioning

confidence: 99%

Section: Middle-levelmentioning

confidence: 99%

Aerial Human Activity Recognition Through a Cognitive Architecture and a New Automata Proposal

Pinto¹,

Melo²,

Marcato³

et al. 2020

Learn. Nonlin. Mod.

Self Cite

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“…This approach is detailed in the architecture presented in Figure 2. The idea is based on [2,42,44]. Some of the data is sent to the supervision devices such as images and the geographical positions.…”

Section: Fog Computingmentioning

confidence: 99%

A Framework for Analyzing Fog-Cloud Computing Cooperation Applied to Information Processing of UAVs

Pinto

Marcato

Melo

et al. 2019

Wireless Communications and Mobile Computing

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Unmanned aerial vehicles (UAVs) are a relatively new technology. Their application can often involve complex and unseen problems. For instance, they can work in a cooperative-based environment under the supervision of a ground station to speed up critical decision-making processes. However, the amount of information exchanged among the aircraft and ground station is limited by high distances, low bandwidth size, restricted processing capability, and energy constraints. These drawbacks restrain large-scale operations such as large area inspections. New distributed state-of-the-art processing architectures, such as fog computing, can improve latency, scalability, and efficiency to meet time constraints via data acquisition, processing, and storage at different levels. Under these amendments, this research work proposes a mathematical model to analyze distribution-based UAVs topologies and a fog-cloud computing framework for large-scale mission and search operations. The tests have successfully predicted latency and other operational constraints, allowing the analysis of fog-computing advantages over traditional cloud-computing architectures.

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“…The middle-level interprets this set of objects, actions, and places that are stemming from the low-level through automata rules. A full explanation is given in Pinto et al (2017). This level is responsible for finding a proper correlation, resulting in the structured description of each frame that will be fed into other automata.…”

Section: Touchmentioning

confidence: 99%

“…Several works individually analyze the required components for those applications, such as computational vision, machine learning, among others. Despite that, a few research works have concerned about the integration of different algorithms and methodologies, which can be done by the use of a high-level cognitive architecture, as the one presented in Pinto et al (2017). Different from the cited work, in this research, the highlevel inference is performed by an expert system, enabling the information organization of different algorithms in a goal-based system.…”

Section: Introductionmentioning

confidence: 99%

Surveillance Architecture for Human Activity Recognition using Unmanned Aerial Vehicle

Pinto

Melo

Marcato

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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There is an intensive growth in researches regarding surveillance and threat detection. Surveillance tasks often involve several actors with multiple interactions. Thus, modeling a complex activity becomes challenging. This work proposes an architecture comprised of low, middle, and high levels. The low-level recognizes characteristics, positioning of objects, and time of occurrences utilizing a camera and Unmanned Aerial Vehicle (UAV) sensors. The middle-level is responsible for structuring the information from the low-level using Deterministic Finite Automata (DFA). An expert system attached in the high-level module performs inference over the organized information to enables the system to have simple reasoning modules, assisting the operator decision. The architecture is embedded in a UAV to reduce the number of cameras and to reach difficult areas. The experiments showed that the proposed system updated the grammatical structure effectively given a sequence of information computed by the vision modules.

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Case-based reasoning approach applied to surveillance system using an autonomous unmanned aerial vehicle

Cited by 23 publications

References 10 publications

Aerial Human Activity Recognition Through a Cognitive Architecture and a New Automata Proposal

Aerial Human Activity Recognition Through a Cognitive Architecture and a New Automata Proposal

A Framework for Analyzing Fog-Cloud Computing Cooperation Applied to Information Processing of UAVs

Surveillance Architecture for Human Activity Recognition using Unmanned Aerial Vehicle

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