Practical optimisation of path planning and completion time of data collection for UAV-enabled disaster communications

2021 ◽  
pp. 143-154
Keyword(s):  
Data Collection ◽  
Path Planning ◽  
Completion Time ◽  
Disaster Communications

scholarly journals Kajian Waktu Penyelesaian Metode Crane Dan Metode Launcher Dalam Pelaksanaan Erection Girder Jembatan (Studi Kasus : Pembangunan Jalan Tol Semarang – Solo Ruas Salatiga – Boyolali Sta 40+409 – Sta 71+785)

2019 ◽  
Vol 24 (1) ◽  
pp. 47
Author(s):  
Farouq Khoirul Izza ◽  
Muhammad Ariya Praditama ◽  
Claudia Nimas Kirana ◽  
Karnawan Joko Setyono ◽  
Sudarmono Sudarmono
Keyword(s):  
Data Collection ◽  
Completion Time ◽  
Secondary Data ◽  
Field Studies ◽  
Development Project ◽  
Primary Data ◽  
Variable Time ◽  
Toll Road ◽  
Road Development ◽  
Road Project

<em><span>The Semarang-Solo Toll Road Project for the Salatiga-Kartasura Section is one part of the Trans Java toll road development project, one of the jobs in the form of an erection girder with the method used, namely the Crane and Launcher methods. The purpose of this study is to compare the completion time between Crane and Launcher Methods with field studies and analysis. Stages of research include literature studies, primary data collection in the form of variable time of completion and secondary data then analyzed by comparing the completion time of the second method of erection girder on girder with a span of 20.8 meters and 40.8 meters. The results of the comparison of completion time were obtained on a 20.8 meter span erection girder seen from the shortest time Crane Method was more efficient 61.44% than the Launcher Method, the longest time Crane Method was more efficient 32.13% of the Launcher Method, and Method average time Crane is more efficient 52.15% than the Launcher Method. Then on the span erection girder 40.8 m seen from the shortest time Crane Method is more efficient 61.48% than the Launcher Method, the longest time Crane Method is more efficient 29.82% than the Launcher Method, and the average time of the Crane Method is more efficient 41, 81% of the Launcher Method.</span></em>

scholarly journals E2PP: An Energy-Efficient Path Planning Method for UAV-Assisted Data Collection

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiang Ji ◽  
Xianjia Meng ◽  
Anwen Wang ◽  
Qingyi Hua ◽  
Fuwei Wang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Collection ◽  
Path Planning ◽  
Greedy Algorithm ◽  
Energy Efficient ◽  
Optimal Path ◽  
Planning Method ◽  
Estimation Model ◽  
Aerial Vehicle ◽  
The Relationship

Using an unmanned aerial vehicle (UAV) to collect data from wireless sensor networks deployed in the field, one of the key tasks is to plan the path for the collection so as to minimize the energy consumption of the UAV. At present, most of the existing methods generally take the shortest flight distance as the optimal objective to plan the optimal path. They simply believe that the shortest path means the least energy consumption of the UAV and ignore the fact that changing direction (heading) can also consume the UAV’s energy in its flight. If the path can be planned based on the UAV’s energy consumption closer to the real situation, the energy consumption of the UAV can be really reduced and its working energy efficiency can be improved. Therefore, this paper proposes a path planning method for UAV-assisted data collection, which can plan an energy-efficient flight path. Firstly, by analyzing the experiment data, we, respectively, model the relationship between the angle of heading change and the energy consumption of the UAV and the relationship between the distance of straight flight and the energy consumption of the UAV. Then, an energy consumption estimation model based on distance and the angle of heading change (ECEMBDA) is put up. By using this model, we can estimate or predict the energy consumption of a UAV to fly from one point (or node) to another (including the start point). Finally, the greedy algorithm is used to plan the path for UAV-assisted data collection according to the above estimated energy consumption. Through simulation and experiments, we compare our proposed method with the conventional method based on pure distance index and greedy algorithm. The results show that this method can obtain data collection path with lower energy consumption and smoother path trajectory, which is more suitable for actual flight.

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