Rapid Plant Development Modelling System for Predictive Agriculture Based on Artificial Intelligence

Actual and upcoming climate changes will evidently have the largest impact on agriculture crop cultivation in terms of reduced harvest, increased costs, and necessary deviations from traditional farming. The aggravating factor for the successful applications of precision and predictive agriculture is the lack of granulated historical data due to slow, year-round cycles of crops, as a prerequisite for further analysis and modeling. A methodology of plant growth observation with the rapid performance of experiments is presented in this paper. The proposed system enables the collection of data with respect to various climate conditions, which are artificially created and permuted in the encapsulated design, suitable for further correlation with plant development identifiers. The design is equipped with a large number of sensors and connected to the central database in a computer cloud, which enables the interconnection and coordination of multiple geographically distributed devices and related experiments in a remote, autonomous, and real-time manner. Over 40 sensors and up to 24 yearly harvests per device enable the yearly collection of approximately 750,000 correlated database entries, which it is possible to independently stack with higher numbers of devices. Such accumulated data is exploited to develop mathematical models of wheat in different growth stages by applying the concepts of artificial intelligence and utilizing them for the prediction of crop development and harvest.

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Greener Economy for Sustainable Development Through AI Intervention

Pradhan,

Malia,

Das

et al. 2023

Handbook of Research on Sustainable Consumption and Production for Greener Economies

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This research chapter deals with understanding the concept of the sustainable ecosystem through the development of a greener economy, and managing the environment for socio-eco environmental growth. The chapter introspects to understand the implication of AI intervention for an eco-friendly economy. It's an exploration into the faces of inclusive growth and equitable equality in life betting natural disasters and environmental degradation towards a greener economy. It explores the cause and effect of climate change for promoting sustainable consumption and production growth and exploration of the potential of AI. The research essentially reviews, analysis, and explores qualitatively and quantitatively the concern of ensuring the consumption of sustainable order through a pattern of production under the ambit of SDG 17. Eventually, it will identify the essential critical factors that can combat the obstacle to greener economy for sustainable consumption by eradicating the restraining forces and measuring barriers that the producer and the consumer encounter towards sustainable peace.

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Rapid Plant Development Modelling System for Predictive Agriculture Based on Artificial Intelligence

Cited by 3 publications

References 18 publications

Synergizing Measurement Science and Artificial Intelligence in Smart Agriculture

Synergizing Measurement Science and Artificial Intelligence in Smart Agriculture

An IoT-Based Encapsulated Design System for Rapid Model Identification of Plant Development

Greener Economy for Sustainable Development Through AI Intervention

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