A Novel LoRa LPWAN-Based Communication Architecture for Search &amp; Rescue Missions

Manuel, Melvin P.; Faied, Mariam; Krishnan, M.

doi:10.1109/access.2022.3178437

Cited by 17 publications

(6 citation statements)

References 22 publications

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“…Manuel et al [ 24 ] suggested a novel communication architecture for a search and rescue (SAR) mission. This architecture is based on the LoRaWAN, and a SAR robot called “Rescuer”, which can be deployed in areas where all communication networks are supposed to be wiped out.…”

Section: Related Workmentioning

confidence: 99%

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention

Boulouard

Ouaissa

et al. 2022

Sensors

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River floods are listed among the natural disasters that can directly influence different aspects of life, ranging from human lives, to economy, infrastructure, agriculture, etc. Organizations are investing heavily in research to find more efficient approaches to prevent them. The Artificial Intelligence of Things (AIoT) is a recent concept that combines the best of both Artificial Intelligence and Internet of Things, and has already demonstrated its capabilities in different fields. In this paper, we introduce an AIoT architecture where river flood sensors, in each region, can transmit their data via the LoRaWAN to their closest local broadcast center. The latter will relay the collected data via 4G/5G to a centralized cloud server that will analyze the data, predict the status of the rivers countrywide using an efficient Artificial Intelligence approach, and thus, help prevent eventual floods. This approach has proven its efficiency at every level. On the one hand, the LoRaWAN-based communication between sensor nodes and broadcast centers has provided a lower energy consumption and a wider range. On the other hand, the Artificial Intelligence-based data analysis has provided better river flood predictions.

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Section: Related Workmentioning

confidence: 99%

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention

Boulouard

Ouaissa

et al. 2022

Sensors

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“…The node challenge ensemble is subscribed to the /camera/image topic so that it can receive the data published by the camera [14] [15]. The data is a message-type Image from the sensor msgs.msg package.…”

Section: A Short Overviewmentioning

confidence: 99%

“…By cutting the lidar [9] signal, it can detect and avoid obstacles. At the same time, we refer to the OpenCV library to realize the visual analysis of the images captured by the camera [10], realize the map drawing through SLAM [11] [12], and realize functions such as autonomous navigation in different areas (challenges). In our experiments, we simulated three different environments as challenges and tested the specific performance of different sensors, as well as autonomous obstacle avoidance and mapping capabilities, using two sensors in each environment alone or in combination.…”

Section: Introductionmentioning

confidence: 99%

ROS-based architecture for robotic automatic mapping and intelligent obstacle avoidance using lidar and cameras

zhao¹,

liu²

2022

International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022)

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With the rapid development of robotics, intelligent obstacle avoidance robots are receiving more and more attention. They are heavily used in all aspects of production and development. The framework we chose to develop this time is based on an open-source platform called Robot Operating System (ROS), which acts as a digital twin in a modular configuration. There are now a large number of robots that choose to complete their architecture under the Robot Operating System (ROS), such as disaster relief robots, somatosensory robots, delivery robots, and more. In this article, we will introduce the ROS architecture of our project. This architecture enables robots to map and navigate autonomously in different environments with different sensors. This article will analyze the architecture we have made and explain the choice to make such an architecture. At the same time, we will also analyze our performance and point out which parts can be improved.

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“…These systems are increasingly employed in a wide array of applications. Their capabilities are demonstrated in search and rescue missions, where multiple robots can cover larger areas faster than a single robot [2][3][4][5]. In surveillance tasks [6], multi-robot systems can monitor larger perimeters, ensuring enhanced security.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Framework and Practical Considerations for Achieving Superior Multi-Robot Exploration: Hybrid Cheetah Optimization with Intelligent Initial Configurations

El Romeh,

Mirjalili

2023

Mathematics

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Efficient exploration in multi-robot systems is significantly influenced by the initial start positions of the robots. This paper introduces the hybrid cheetah exploration technique with intelligent initial configuration (HCETIIC), a novel strategy explicitly designed to optimize exploration efficiency across varying initial start configurations: uniform distribution, centralized position, random positions, perimeter positions, clustered positions, and strategic positions. To establish the effectiveness of HCETIIC, we engage in a comparative analysis with four other prevalent hybrid methods in the domain. These methods amalgamate the principles of coordinated multi-robot exploration (CME) with different metaheuristic algorithms and have demonstrated compelling results in their respective studies. The performance comparison is based on essential measures such as runtime, the percentage of the explored area, and failure rate. The empirical results reveal that the proposed HCETIIC method consistently outperforms the compared strategies across different start positions, thereby emphasizing its considerable potential for enhancing efficiency in multi-robot exploration tasks across a wide range of real-world scenarios. This research underscores the critical, yet often overlooked, role of the initial robot configuration in multi-robot exploration, establishing a new direction for further improvements in this field.

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A Novel LoRa LPWAN-Based Communication Architecture for Search & Rescue Missions

Cited by 17 publications

References 22 publications

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention

ROS-based architecture for robotic automatic mapping and intelligent obstacle avoidance using lidar and cameras

Theoretical Framework and Practical Considerations for Achieving Superior Multi-Robot Exploration: Hybrid Cheetah Optimization with Intelligent Initial Configurations

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