FEATURE
INGENIEUR
FEATURE
INGENIEUR
3D Modelling for the Agrifood Industry
By Dr Hazreen Haizi Harith Assoc . Prof . Dr Samsuzana Abd Aziz Chong Jia En Ademola Aina
Smart Farming Technology Research Center , Faculty of Engineering , Universiti Putra Malaysia .
Three-dimensional ( 3D ) modelling has revolutionised various fields by providing accurate , detailed visual representations of real-world objects and environments . Its applications in engineering for monitoring purposes are well-established . For example , in building monitoring , 3D models enable precise inspections , facilitating the identification and rectification of structural issues to enhance safety and efficiency . In the agrifood industry , 3D modelling allows for detailed analysis of crop growth , soil conditions , and irrigation patterns , promoting precision farming and post-harvest practices that optimise output and resource use . The technology also supports advanced simulations and predictions , enabling evidence-based management and decision-making in both sectors . 3D modelling ’ s ability to capture and analyse complex data sets makes it an invaluable tool across diverse applications . This article aims to demonstrate the use of 3D modelling for crop monitoring and post-harvest handling , highlighting their contribution to enhancing precision agriculture and enabling data-driven decision-making , ultimately improving outcomes for all stakeholders in the agrifood value chain .
3D modelling techniques refer to the methods and processes used to create 3D representations of objects or environments . In the context of crop growth monitoring , these techniques enable the visualisation and analysis of plant structures , allowing precise measurements and assessments to inform agricultural practices . The fundamental principles of 3D modelling include accurate data collection , precise data processing , and detailed visualisation .
Accurate data collection involves capturing spatial information using technologies like LiDAR , photogrammetry and laser scanning , ensuring that the model reflects real-world dimensions and features . Precise data processing is crucial to convert raw data into usable 3D models , involving steps such as noise reduction , point cloud generation , and mesh creation . Detailed visualisation allows for the inspection and analysis of complex objects , enabling users to identify and address issues effectively .
In agricultural settings , one unique challenge is the dynamic and changing nature of the environment . Crops grow and change shape over time , requiring timely data collection and updates to the 3D models . Additionally , factors such as varying light conditions , weather , and seasonal changes can affect the quality and consistency of data collection . Furthermore , agricultural settings often span large areas . UAVs or drones can be used for data collection in open areas , while mobile and compact 3D image-capturing technologies are more suitable for indoor environments .
36 VOL 99 JULY - SEPTEMBER 2024