Impact of sensor mobility on UAV-based smart farm communications

Nintanavongsa, Prusayon; Pitimon, Itarun

doi:10.1109/ieecon.2017.8075822

Cited by 16 publications

(12 citation statements)

References 5 publications

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“…Unmanned Aerial Vehicles (UAVs) play a significant role in smart farming system by providing imagery analysis and agricultural surveillance as well as on-demand communication [65]. UAVs are applied in [66] to perform vegetation detection, plant-tailored feature extraction and classification to estimate the distribution of crops and weeds in the field.…”

Section: A Current and Future Applications Of Multi-agent Cloud Roboticsmentioning

confidence: 99%

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

Afrin

Jin

Rahman

et al. 2021

IEEE Commun. Surv. Tutorials

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Robotic applications nowadays are widely adopted to enhance operational automation and performance of real-world Cyber-Physical Systems (CPSs) including Industry 4.0, agriculture, healthcare, and disaster management. These applications are composed of latency-sensitive, data-heavy, and compute-intensive tasks. The robots, however, are constrained in the computational power and storage capacity. The concept of multi-agent cloud robotics enables robotto-robot cooperation and creates a complementary environment for the robots in executing large-scale applications with the capability to utilize the edge and cloud resources. However, in such a collaborative environment, the optimal resource allocation for robotic tasks is challenging to achieve. Heterogeneous energy consumption rates and application of execution costs associated with the robots and computing instances make it even more complex. In addition, the data transmission delay between local robots, edge nodes, and cloud data centres adversely affects the real-time interactions and impedes service performance guarantee. Taking all these issues into account, this paper comprehensively surveys the state-of-the-art on resource allocation and service provisioning in multi-agent cloud robotics. The paper presents the application domains of multi-agent cloud robotics through explicit comparison with the contemporary computing paradigms and identifies the specific research challenges. A complete taxonomy on resource allocation is presented for the first time, together with the discussion of resource pooling, computation offloading, and task scheduling for efficient service provisioning. Furthermore, we highlight the research gaps from the learned lessons, and present future directions deemed beneficial to further advance this emerging field.

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Section: A Current and Future Applications Of Multi-agent Cloud Roboticsmentioning

confidence: 99%

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

Afrin

Jin

Rahman

et al. 2021

IEEE Commun. Surv. Tutorials

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“…tp and Constraint (10) is satisfied for all paths in C because we have the optimal solution of the current master problem.…”

Section: Pricing Problemmentioning

confidence: 99%

“…In the following, we seek to find if it exists new trajectories in the FANET violating Constraints (10). This is the goal of the pricing problem.…”

Section: Pricing Problemmentioning

confidence: 99%

“…If such path exists, we add it to the current set C of variables of the master problem. If there is no new trajectory violating (10), then the separationoptimization theorem ensures that we have reached the optimal solution of the relaxed master program.…”

Section: Pricing Problemmentioning

confidence: 99%

“…1. Drones networks can also be applied to smart farming where mobile sensor robots roam the fields to gather data on soil humidity, temperature, crops quality and perimeter monitoring [10,16]. In rural areas with poor cellular coverage, establishing a reliable and constant connection between the sensors and a fixed base station for processing can be challenging.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing FANET deployment for mobile sensor tracking in disaster management scenario

Silva

Caillouet

Coudert

2021

2021 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)

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This paper addresses the data collection problem using the minimum number of unmanned aerial vehicles (UAVs) in a disaster management scenario where mobile sensors are investigating the devastated area. Critical information needs to be quickly gathered for processing by the rescue team, so the use of UAVs in this situation is of great interest. We propose an optimal model for computing the trajectories of the UAVs while guaranteeing the total coverage of the ground mobile sensors and connectivity among the UAVs with a central base station dedicated to data processing. Our model is based on a decomposition model and is solved effectively using column generation. We show that we can provide a plan for deploying the UAVs minimizing the total traveled distance.

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