Online drone-based data gathering strategies for ground sensor networks

Abstract

This paper proposes two path-planning schemes for data collection in WSN using a drone flying over the sensor nodes to collect their data. We assign a weight to each sensor node corresponding to its priority in the collection process. When the drone selects its destination node, it will choose the one having the highest weight. We have defined utility functions based on the sensor nodes' information disseminated in the Wireless Sensor Network (WSN) using the Optimized Link State Routing protocol (OLSR). The information required to compute the nodes' weight is added to the exchanged packets during the execution of OLSR. The first proposed strategy is Data-driven Data Gathering Strategy (DDG) which uses the amount of stored data in each sensor node buffer. A priority is given to the nodes having the most significant data amount to collect. The second strategy is called Time-driven Data Gathering Strategy (TDG) where the age of the data is considered.

Reinforcement Learning-based Topology-Aware Routing Protocol with Priority Scheduling for Internet of Drones in Agriculture Application

“…Using a drone to float over the IoT devices and gather data, [18] provides two route strategies for data gathering in WSN. Every sensor node is assigned a weight based on its importance during the data collection process.…”

An Overview to Unmanned Aerial Vehicles from Perspectives of Quality and Safety Management in Aviation

“…• Delivering medicine, food and water to the injured Schweizer et al, (2018) • Taking images of areas or infrastructures for damage assessment after disasters Yanchao Liu, (2019) • Food delivery Delivery of Goods Bhatt et al, (2018) • Medicine and blood samples delivery Sumanth Reddy et al, (2019) • Lightweight commercial products delivery Ghazali et al, (2021) • Network gateways Providing Wireless Coverage Wu et al, (2021) • Omnipresent coverage Tazibt et al, (2022) • Data collection S. K. Khan et al, (2021) • Relay nodes between wireless devices Fu et al, (2020) • Crop maturity and yield mapping Precision Agriculture Christiansen et al, (2017) • Field tile mapping Romero et al, (2018) • Irrigation scheduling Faiçal et al, (2017) • Pesticide spraying Kerkech et al, (2020) • Disease detection Stroppiana et al, (2018) • Weed detection Huuskonen & Oksanen, (2018) • Soil texture mapping Kavoosi et al, (2020) • Residue cover and tillage mapping Kas & Johnson, (2020) • Infrastructure internal inspection Infrastructure Inspection Gopalakrishnan et al, (2018) • Surface degradation assessment and crack detection Tan et al, (2021) • Vertical inspection for towers and high rise Jalil et al, (2019) • Power transmission lines inspection Gu et al, (2020) • Wind and oil/gas turbine inspection Nordin et al, (2022) • Onshore and offshore asset inspection Other than their operational purposes, the types of UAVs also differ according to their design features which affect their flying principles. In Figure 5, UAV types are classified first according to their vehicle mass, then the heavy types are further classified to rotor and wing types (Liew et al, 2017).…”