Computer Vision Applications are Transforming Pest Control
Advances in machine learning and computer vision technology are beginning to impact a surprisingly diverse array of industries. Automated systems have the capacity to extend the reach of researchers and companies, acting as a force multiplier that greatly improves efficiency.
Pest control is one sector that is beginning to recognize the potential of AI powered automation. Controlling harmful pests is as important for individual homeowners as it is for big agriculture. Changes in our climate are causing new pest species to make their presence felt in previously unaffected regions. As a result the need for effective pest control has never been more pressing.
This blog will examine three emerging use cases for AI in pest control. The foundation of each of these applications is annotated training data. Keymakr is collaborating with developers by providing effective annotation services.
Controlling insect populations
In 2018 mosquitoes were responsible for 830,000 deaths. Despite the huge numbers, this represents a significant reduction in lives lost to this disease transmitting insect. Through the combined efforts of governments, NGOs, and the private sector advances have been made in antimalarial drugs and the distribution of mitigating products like mosquito nets.
Computer vision AI could be part of the next fight against mosquito spread disease by helping to control insect populations. Mosquito numbers can be controlled by releasing large numbers of sterile male mosquitoes, who mate with females and reduce the overall population. Machine learning allows researchers to determine the sex of mosquitoes at the larval stage.
Mosquitoes later in their development are much harder to transport and deploy. This means that the insects can be easily bred and transported to the places they can have an impact.
This kind of effective recognition is made possible by annotated training data. AI models can learn to distinguish the sex of mosquitoes through exposure to thousands of labeled images of larvae. Creating these datasets means collaborating with experts in the field and ensuring accuracy through verification processes.
Automated home pest inspections
Pest control for private homes and businesses is a large service industry that helps people to remove unwelcome insects and rodents from their properties. Most pest control companies perform property inspections as a way of assessing pest problems and creating business leads.
Drones are now being deployed to improve the efficiency and thoroughness of these inspections. Machine learning models can be integrated into remote controlled drones, allowing operators to access hard to reach areas and spot pests that might be missed during routine inspections. These integrated systems can alert drone operators when they identify targeted pest types, extending the effective field of vision of the pest controller.
Varied datasets are vital if this technology is to fulfill its potential. Low light conditions and differing video quality must all be represented in the annotated data. Working with annotation providers, like Keymakr, can ensure that these needs are met in a cost-effective manner.
Assessing insect numbers
Counting the number of insects of various species present in an area is important for planning pest control, and for guiding agricultural policy. However, when researchers attract insects to a site for counting it can mean thousands of individual animals all of which need to be identified and logged.
This is, of course, a tremendously time-consuming process, one which AI is well equipped to take over. Automated counting stations can send real time information on insect numbers, in turn allowing farmers to determine whether or not pesticides should be used.
Controlling potentially destructive pests requires annotated datasets. Keymakr works with pioneers in multiple industries to create image and video data that does not compromise on quality or precision.
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