Autonomous surveillance for biosecurity.
The global movement of people and goods has increased the risk of biosecurity threats and their potential to incur large economic, social, and environmental costs. Conventional manual biosecurity surveillance methods are limited by their scalability in space and time. This article focuses on autonomous surveillance systems, comprising sensor networks, robots, and intelligent algorithms, and their applicability to biosecurity threats. We discuss the spatial and temporal attributes of autonomous surveillance technologies and map them to three broad categories of biosecurity threat: (i) vector-borne diseases; (ii) plant pests; and (iii) aquatic pests. Our discussion reveals a broad range of opportunities to serve biosecurity needs through autonomous surveillance.
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia. Electronic address: rjurdak@ieee.org.
Raja
R
Jurdak
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia.
Alberto
A
Elfes
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia.
Branislav
B
Kusy
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia.
Ashley
A
Tews
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia; University of New South Wales, School of Computer Science and Engineering, Sydney, NSW 2052, Australia.
Wen
W
Hu
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia.
Emili
E
Hernandez
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia.
Navinda
N
Kottege
CSIRO, 1 Technology Court Pullenvale, QLD 4069, Australia.
Pavan
P
Sikka
D018556:Crops, Agricultural; D004784:Environmental Monitoring / Q000295:instrumentation*; D012371:Robotics / Q000295:instrumentation*; D012637:Security Measures
autonomy; distributed; robots; sensors; spatiotemporal; systems