Smartphone app tracks invasive plants

Smartphone app tracks invasive plants

Bristol University (Bristol, UK) researchers have developed a new mobile phone app to help the public track the spread of invasive plants that pose a threat to biodiversity.

The so-called "PlantTracker" app shows people how to use their smartphones to identify and record where they have spotted Japanese Knotweed, Himalayan Balsam and Floating Pennywort - three particularly problematic Invasive, Non-Native Species (INNS) that are causing untold problems in the UK.  Once they have done so, they can submit geo-located photos that can then be analyzed by the researchers.

The project is being piloted in the Midlands initially, but it is hoped that in subsequent years it will be expanded to cover the whole of the UK. Records can be submitted from outside the Midlands at present, but they may not be analyzed immediately.

"Engaging members of the public with scientific research is an exciting and expanding area with benefits both to science and the individuals involved," says Bristol University’s Dave Kilbey, whose team aims to build a portfolio of apps to tackle other environmental problems.

The PlantTracker app is available free from the iTunes App Store and Google Play Store by searching for planttracker (one word), or from the website here.

-- by Dave Wilson, Senior Editor, Vision Systems Design

Image processing systems are widely deployed in agricultural and horticultural environments. Here are five of the top stories that Vision Systems Design has published on the subject over the past year.


1. Camera-guided lasers zap weeds

Researchers at the Laser Zentrum Hannover (LZH; Hannover, Germany) and the Biosystems and Horticultural Engineering faculty of the Leibniz Universität Hannover (Hannover, Germany) are developing a system that uses a camera-guided laser to fight weeds.

2. Robotic image-processing system analyzes plant growth

Researchers at the University of Wisconsin–Madison (Madison, WI, USA) have developed an image-processing system that captures time-lapse images of how plants grow.

3. Cameras get to the root of global warming

Researchers at the Oak Ridge National Laboratory (Oak Ridge, TN) are to use a system of minirhizotrons to examine the effects on elevated temperatures and levels of carbon dioxide on the roots of plants in wetlands.

4. Vision-guided robot automates vegetation analysis

At the University of Illinois at Urbana-Champaign (Urbana, IL, USA) and United States Department of Agriculture (USDA; Wooster, OH, USA), Dr. Hongyoung Jeon and his colleagues have developed a machine-vision-based system that uses adaptive image segmentation and neural networks to identify vegetation varieties.

5. Imaging fights invasive plants in cultivated fields and makes agriculture greener

Researchers at Wageningen University in the Netherlands have developed a machine-vision-based system to automatically recognize and combat weeds in the field. The result will be increased productivity, reduced costs, and less impact on the environment.

Webcasts

Vision technologies for robotics: Application do’s and don’ts

This webcast will offer tips and examples for integration of machine vision systems in robotics applications. Expert Jeff Boeve of JR Automation will explain how to clearly define your pass/fa...

Solving factory automation challenges with machine vision

What do you need to know to implement your machine vision setup for industrial automation? This webcast will answer that question using real-world application examples—such as inspection, assembly,...

Performing effective 2D and 3D pattern matching in machine vision applications

This webcast, sponsored by MVTec, will explain how pattern matching works and in what applications is being used.

Overcoming the Limitations of Vision Systems in Manufacturing

Expert speaker Jim Blasius, Solutions Architect, Measurement & Automation Product Group at ADLINK Technology will examine the pros and cons of different compact vision systems, discuss current ...

Archives

Click here to view archived Vision Systems Design articles