Dronesourcing: a modular, expandable multi-sensor UAV platform for combined, real-time environmental monitoring

ABSTRACT The systematic environmental monitoring of the land, atmosphere, oceans and their coupling zones, is assisted by the use of unmanned aerial vehicles (UAVs) that can operate over rural and/or urban areas to provide enhanced spatial and temporal measurement resolutions compared against corresponding satellite products. The international UAV market includes a vast number of solutions that carry sensors for environmental monitoring varying in type, flight time, carrying weight, communication, and autonomous flight. The majority of these commercial UAVs (especially the low-cost ones) have been designed for specific applications and their main disadvantage is that they can only integrate the payload they have been initially designed to carry, thus presenting minimal modularity. This work presents a modular and affordable platform where the user can easily adapt almost any type of environmental monitoring sensor, which can transmit its measurements to the UAV flight controller without the need for any additional modification. A novel communication protocol has been developed that is also capable to incorporate proximity sensors for collision avoidance. In addition, a wireless mobile telecommunications module incorporation through the use of mobile devices on the UAV provides real-time animated map generation along with cooperative capabilities for fleet missions.

[1]  Costas A. Varotsos,et al.  Atmospheric greenhouse effect in the context of global climate change , 1995 .

[2]  Qihao Weng,et al.  Remote Sensing Sensors and Applications in Environmental Resources Mapping and Modelling , 2007, Sensors.

[3]  Gene E. Likens,et al.  Who needs environmental monitoring , 2007 .

[4]  Mashrur Chowdhury,et al.  Attack of the Drones , 2007 .

[5]  Giancarmine Fasano,et al.  Multi-Sensor-Based Fully Autonomous Non-Cooperative Collision Avoidance System for Unmanned Air Vehicles , 2008, J. Aerosp. Comput. Inf. Commun..

[6]  Reg Austin,et al.  Unmanned Aircraft Systems: Uavs Design, Development and Deployment , 2010 .

[7]  Kang Sun,et al.  Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles , 2012, Remote. Sens..

[8]  Wikimedia Commons,et al.  A new eye in the sky: Eco-drones , 2013 .

[9]  Annette Mossel,et al.  Autonomous Flight using a Smartphone as On-Board Processing Unit in GPS-Denied Environments , 2013, MoMM '13.

[10]  Michael J. Logan,et al.  Intelligent control of Unmanned aerial vehicle using inertial guidance Algorithm , 2013 .

[11]  Radhakant Padhi,et al.  Reactive Collision Avoidance of UAVs with Vision Sensing using Pin-hole Cameras , 2013 .

[12]  Allistair A. Moses,et al.  RADAR Based Collision Avoidance for Unmanned Aircraft Systems , 2013 .

[13]  P. Ceccato,et al.  Climate and environmental monitoring for decision making , 2014 .

[14]  WhiteheadKen,et al.  Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: a review of progress and challenges1 , 2014 .

[15]  Brett C. Eaton,et al.  Remote sensing of the environment with small unmanned aircraft systems (UASs), part 2: scientific and commercial applications , 2014 .

[16]  D. Bird,et al.  Wildlife research and management methods in the 21st century: Where do unmanned aircraft fit in?1 , 2015 .

[17]  Tianjiang Hu,et al.  Employing smartphone as on-board navigator in unmanned aerial vehicles: implementation and experiments , 2015, Ind. Robot.

[18]  Antonio Barrientos,et al.  Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses , 2015, Sensors.

[19]  Yan Guo,et al.  Forest Fire Detection Solution Based on UAV Aerial Data , 2015 .

[20]  Vijay Kumar,et al.  Devices, systems, and methods for automated monitoring enabling precision agriculture , 2015, 2015 IEEE International Conference on Automation Science and Engineering (CASE).

[21]  Leticia A. Neira Tovar,et al.  Instrumentation of an Array of Ultrasonic Sensors and Data Processing for Unmanned Aerial Vehicle (UAV) for Teaching the Application of the Kalman Filter , 2015 .

[22]  Abdelfettah Belghith,et al.  A Review on Collision Avoidance Systems for Unmanned Aerial Vehicles , 2015, Nets4Cars/Nets4Trains/Nets4Aircraft.

[23]  Sergio Montenegro,et al.  Obstacle Detection and Collision Avoidance for a UAV With Complementary Low-Cost Sensors , 2015, IEEE Access.

[24]  Konstantinos Dalamagkidis.  Classification of UAVs , 2015 .

[25]  Jianya Gong,et al.  Real-time GIS data model and sensor web service platform for environmental data management , 2015, International Journal of Health Geographics.

[26]  O. Trindade,et al.  MISSION-ORIENTED SENSOR ARRAYS AND UAVs – A CASE STUDY ON ENVIRONMENTAL MONITORING , 2015 .

[27]  Sunny Bhardwaj,et al.  Sensor System Implementation for Unmanned Aerial Vehicles , 2015 .

[28]  Scott A. Smolka,et al.  A survey on unmanned aerial vehicle collision avoidance systems , 2015, ArXiv.

[29]  Øyvind Ødegård,et al.  Integrated environmental mapping and monitoring, a methodological approach to optimise knowledge gathering and sampling strategy. , 2015, Marine pollution bulletin.

[30]  A. Bolten,et al.  MULTI-TEMPORAL CROP SURFACE MODELS COMBINED WITH THE RGB VEGETATION INDEX FROM UAV-BASED IMAGES FOR FORAGE MONITORING IN GRASSLAND , 2016 .

[31]  Naser El-Sheimy,et al.  DESIGN AND IMPLEMENTATION OF A LOW-COST UAV-BASED MULTI-SENSOR PAYLOAD FOR RAPID-RESPONSE MAPPING APPLICATIONS , 2016 .

[32]  P. Kanaroglou,et al.  Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models. , 2016, Journal of environmental management.

[33]  Jon Birger Skjærseth,et al.  Conclusions and the road ahead , 2016 .

[34]  sadamhusen.  Arduino Pro Mini , 2016 .

[35]  Luis Felipe Gonzalez,et al.  An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives , 2016, Sensors.

[36]  Peter Nguyen.  Developing an Unmanned Aerial Vehicle (UAV) multi-sensor payload carrier for air quality monitoring , 2016 .

[37]  S. Hancock,et al.  A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones , 2016, PloS one.