Evolutionary Approach for Automatic Generation of Multi-Objective Morphological Filters for Depth Images in Embedded Navigation Systems

Dourado, Antonio Miguel Batista; Pedrino, Emerson Carlos

doi:10.1109/tla.2020.9099775

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…In the same way, the smart devices aim to improve the life of Visually Impaired Peoples. [1][2][3] The main challenging every visually impaired person face is navigation and obstacle detection. With the advancements of IoT, now it becomes easier through many sensors like ultrasonic, accelerometer etc.…”

Section: Introductionmentioning

confidence: 99%

Multi-obstacle aware smart navigation system for visually impaired people in fog connected IoT-cloud environment

Mueen

Awedh

Zafar

2022

Health Informatics J

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Design of smart navigation for visually impaired/blind people is a hindering task. Existing researchers analyzed it in either indoor or outdoor environment and also it’s failed to focus on optimum route selection, latency minimization and multi-obstacle presence. In order to overcome these challenges and to provide precise assistance to visually impaired people, this paper proposes smart navigation system for visually impaired people based on both image and sensor outputs of the smart wearable. The proposed approach involves the upcoming processes: (i) the input query of the visually impaired people (users) is improved by the query processor in order to achieve accurate assistance. (ii) The safest route from source to destination is provided by implementing Environment aware Bald Eagle Search Optimization algorithm in which multiple routes are identified and classified into three different classes from which the safest route is suggested to the users. (iii) The concept of fog computing is leveraged and the optimal fog node is selected in order to minimize the latency. The fog node selection is executed by using Nearest Grey Absolute Decision Making Algorithm based on multiple parameters. (iv) The retrieval of relevant information is performed by means of computing Euclidean distance between the reference and database information. (v) The multi-obstacle detection is carried out by YOLOv3 Tiny in which both the static and dynamic obstacles are classified into small, medium and large obstacles. (vi) The decision upon navigation is provided by implementing Adaptive Asynchronous Advantage Actor-Critic (A3C) algorithm based on fusion of both image and sensor outputs. (vii) Management of heterogeneous is carried out by predicting and pruning the fault data in the sensor output by minimum distance based extended kalman filter for better accuracy and clustering the similar information by implementing Spatial-Temporal Optics Clustering Algorithm to reduce complexity. The proposed model is implemented in NS 3.26 and the results proved that it outperforms other existing works in terms of obstacle detection and task completion time.

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Section: Introductionmentioning

confidence: 99%

Multi-obstacle aware smart navigation system for visually impaired people in fog connected IoT-cloud environment

Mueen

Awedh

Zafar

2022

Health Informatics J

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“…E-commerce is a modern business operation mode with network as the platform, information technology as the means and economic benefits as the center [1]. E-commerce has changed the business philosophy, management methods and means of payment of enterprises.…”

Section: Introductionmentioning

confidence: 99%

Multi Objective Enhancement Method for Embedded Software Quality of e-Commerce Platform Based on Firefly Algorithm Optimization

Jiang

Guo

et al. 2021

IEEE Access

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Embedded software is the basic guarantee for the safe and stable operation of e-commerce platform. In order to improve the embedded software quality of e-commerce platform, a multi-objective enhancement method based on firefly algorithm optimization is proposed. Based on the two-dimensional strengthening model of embedded software duration cost of e-commerce platform, the application effect of embedded software is quantified by setting multi-level index system, so that the application effect of embedded software is included in the strengthening target. On this basis, the multi-objective strengthening model of embedded software duration, cost and application effect is constructed. The firefly algorithm is used to solve the multi-objective enhancement model, and the firefly algorithm is optimized by constraint priority non inferior ranking. The optimal compromise solution is selected according to the fuzzy membership degree in fuzzy mathematics. Experimental results show that the proposed method can significantly improve the quality of embedded software of e-commerce platform.

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Obstacle avoidance for orchard vehicle trinocular vision system based on coupling of geometric constraint and virtual force field method

Liu

Wang

et al. 2022

Expert Systems with Applications

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Evolutionary Approach for Automatic Generation of Multi-Objective Morphological Filters for Depth Images in Embedded Navigation Systems

Cited by 4 publications

References 29 publications

Multi-obstacle aware smart navigation system for visually impaired people in fog connected IoT-cloud environment

Multi-obstacle aware smart navigation system for visually impaired people in fog connected IoT-cloud environment

Multi Objective Enhancement Method for Embedded Software Quality of e-Commerce Platform Based on Firefly Algorithm Optimization

Obstacle avoidance for orchard vehicle trinocular vision system based on coupling of geometric constraint and virtual force field method

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