Nowadays, with the development of sustainable and intelligent phytoprotection, more and more research incorporate intelligent computing and Internet of Things (IoT), which can be inspired by biological behaviors and can be a good aid to the research of plant conservation. Methods such as evolutionary computation and swarm intelligence have solved many practical problems by designing algorithms that simulate animal behaviors such as predation and reproduction. For example, the Particle Swarm Optimization (PSO) algorithm was proposed by studying the behavior of bird predation. The Ant Colony Optimization (ACO) algorithm was proposed by studying the bioinformatics principle of foraging route selection of ants. The Artificial Bee Colony (ABC) algorithm was proposed by studying the honeybee honey-harvesting behavior. The genetic algorithm (GA) was proposed by studying the principles of gene crossover and mutation. All these algorithms are based on the results of bioinformatics theory, but they are mostly based on the biological behavior of animals. Moreover, in IoT technologies, a large number of sensors are used for the detection of ecological environments, biological growth environments, or animal behavior, but few instruments are used for the detection and evaluation of plant growth processes, mostly playing a supporting role. By studying these technologies, we can also contribute to the development of biotechnology. For example, genetic algorithms (GA) to guide plant breeding and reproduction, bee colony intelligence to simulate plant reproduction processes for biological control, and sensors to control the environment and range of plants to select breeding sites.
Currently, bioinformatics has produced some integration with the field of intelligent computing, but the research area is mostly applied. This topic will focus on the inspiration of intelligent computing from biotechnology and the reapplication of these enlightening studies in biotechnology. Contributions and comments on the latest research under this topic are welcome.
Potential topics may include, but are not limited to, the following:
- Swarm intelligence algorithm-guided invasion control techniques for plant species.
- Evolutionary computation-guided plant mating techniques.
- Plant protection techniques using sensor networks.
- Swarm intelligence algorithms guided by plant propagation processes.
- Genetic algorithm guided by plant propagation process.
- Sensor design methods guided by plant propagation process or plant growth.
Nowadays, with the development of sustainable and intelligent phytoprotection, more and more research incorporate intelligent computing and Internet of Things (IoT), which can be inspired by biological behaviors and can be a good aid to the research of plant conservation. Methods such as evolutionary computation and swarm intelligence have solved many practical problems by designing algorithms that simulate animal behaviors such as predation and reproduction. For example, the Particle Swarm Optimization (PSO) algorithm was proposed by studying the behavior of bird predation. The Ant Colony Optimization (ACO) algorithm was proposed by studying the bioinformatics principle of foraging route selection of ants. The Artificial Bee Colony (ABC) algorithm was proposed by studying the honeybee honey-harvesting behavior. The genetic algorithm (GA) was proposed by studying the principles of gene crossover and mutation. All these algorithms are based on the results of bioinformatics theory, but they are mostly based on the biological behavior of animals. Moreover, in IoT technologies, a large number of sensors are used for the detection of ecological environments, biological growth environments, or animal behavior, but few instruments are used for the detection and evaluation of plant growth processes, mostly playing a supporting role. By studying these technologies, we can also contribute to the development of biotechnology. For example, genetic algorithms (GA) to guide plant breeding and reproduction, bee colony intelligence to simulate plant reproduction processes for biological control, and sensors to control the environment and range of plants to select breeding sites.
Currently, bioinformatics has produced some integration with the field of intelligent computing, but the research area is mostly applied. This topic will focus on the inspiration of intelligent computing from biotechnology and the reapplication of these enlightening studies in biotechnology. Contributions and comments on the latest research under this topic are welcome.
Potential topics may include, but are not limited to, the following:
- Swarm intelligence algorithm-guided invasion control techniques for plant species.
- Evolutionary computation-guided plant mating techniques.
- Plant protection techniques using sensor networks.
- Swarm intelligence algorithms guided by plant propagation processes.
- Genetic algorithm guided by plant propagation process.
- Sensor design methods guided by plant propagation process or plant growth.
