Today, more than 50% of the world's population lives in cities. Projection from the United Nations#1 shows that two-thirds of the population on earth in 2050 will be living in urbanised metropolitan areas. Hence traditional agriculture could
no longer support the need for fresh and healthy food for megacities. One potential solution is Urban Farming: growing crops in big cities.
The advantages offered by these urban farming concepts have already made their way into modern cities. In recent years, the creation of urban farming technologies could be seen in many big cities around the world, including Singapore. To increase the
resilience of the food supply chain, Singapore has developed its own approach by identifying them as "three food baskets": Diversifying food sources, Growing locally, and Growing overseas. Through “growing locally”, the policy makers have
formulated a "30 by 30" plan to build up Singapore’s food industry's capacity and to have 30% of Singapore's nutritional needs produced locally by 2030. To support Singapore’s mission and address challenges such as food security and sustainability,
A*STAR’s Institute of High Performance Computing (IHPC) developed an intelligent urban farm model - iSAM that integrates lighting simulation, light recipe optimisation, and farm performance simulation and evaluation, helping
farmers to study their crops’ health, lighting recommendations, and farm design optimisation for shorter growth and higher harvest cycle.
Features
The integrated smart farm model (iSAM) currently includes the following four modules:
- Layout based hybrid lighting farm design (FarmMAP): Propose farm design with light recipes in a dynamic environment with inputs of sensor data to evaluate the potential yield of the farm
- Lighting modelling and simulation (GrowLITE): Optimise lighting environment for farms and assess and recommend hybrid lighting strategies for greenhouses by considering farm structure, light recipe of crops, energy usage, etc.
- Crop growth cycle simulation (CropSIM): Simulate the full crop growth cycle with light recipes of different plant stages and crop growth rates under dynamic environmental conditions
- Biomass prediction and optimal light recipe (HarvestAI): Train artificial intelligence (AI) model to predict the biomass of plants and recommend the light recipe for optimal plant growth
The Science Behind
iSAM is an intelligent platform that could help modern farmers study their crops’ health, lighting recommendations, and farm design optimisation for shorter growth and higher harvest cycle.
Fig 1. Farm design modelling and optimisation
FarmMAP creates and visualises the farm object and layout. By serialising the farm objects, it communicates with other modules for evaluating the light distribution and intensity inside the farm and the potential crop yield, to achieve an optimal farm design (Fig 1).
Fig 2: Light distribution and intensity on crops of a typical day
GrowLITE simulates the light spectrums in terms of wavelength ranges and intensity by considering natural light and/or artificial light to understand the light distribution and the amount of light a crop in the farm can receive (Fig 2).
Fig 3: Crop growth cycle simulation
CropSIM evaluates the farm design by estimating the monthly or yearly yield under various environmental factors, including light conditions and crop light recipes through an agent-based simulation module (Fig 3).
Fig 4: AI models for biomass prediction and optimisation of light recipe
HarvestAI analyses the experimental and/or existing crop growth data and predicts crop growth rates. It also recommends the optimal light recipe using an AI-based recommendation engine (Fig 4).
The developed technologies can equip the
farmers to best utilise the limited natural resources such as land and space in the urban environment to increase crop production. In addition, with better yield and using lesser energy by applying optimal lighting recipe, it results in lower carbon
footprints.
Industry Applications
The iSAM platform is a smart farm modelling platform for optimising the crop yield and potentially helping balance the energy utilisation and emission.
- Agritech – Indoor farms, greenhouse, rooftop farms
- Farm Design – Energy efficiency, layout optimisation
- Energy – Energy computation and optimisation, net zero energy usage
- Recycling and sustainability - alternative energy applications