aiTree Ltd has been focusing on systematic technologies to solve Demand & Supply problems with Artificial Intelligence algorithms for over 25 years. The typical application Forest Simulation Optimization System (FSOS) has been applied and improved for over 20 years in British Columbia, Canada. The demands from a forest include wildlife habitat, biodiversity, water quality, visual quality, carbon storage, timber production and economic contributions. FSOS focuses on both “what we can take from the forest” and “what we can create in the forest”. Forest design is the most complicated problem because the trees are growing and dying, and all the values have to be considered every year for over 400 years. FSOS is a good example that uses Artificial Intelligence, Big Data and Cloud computing technologies to solve the complicated Demand & Supply problems. You can find more information in the Canadian forest cloud: http://forestcloud.ca and in the Chinese forest cloud: http://forestcloud.cn.
We are a group of people who believe that the systematic approach can let you save resources, protect environment, and make more profit. We have a lot of experience of using new technologies such as Artificial Intelligence, Big Data, Cloud Computing to integrate long-term strategies and short-term operations. The main principles are: consider long-term targets and short-term demands simultaneously; consider the big area pictures and small local region demands simultaneously; and consider all layer resources simultaneously.
We have been working with artificial intelligence, big data, HPC cloud computing, and system engineering for decades, bringing business intelligence to designing, planning and optimizing land assets in forestry, utilities and other resource sectors.
FSOS is developed for multiple-objective forest analysis and planning, it integrates long-term strategic planning and short-term operation planning in one model. It is a great tool for forest management simulations, animations and optimizations. You can compare management scenarios and see the future forests with different management scenarios.
We have developed a forest Carbon Analysis and Accounting System FSOS-C based on Forest Simulation
Optimization System (FSOS).
Unlike other forest carbon accounting system, FSOS-C can not only calculate carbon amounts stored in different pools such as stands, wood products, floor, and soil with different stand dynamics and management scenarios, but also optimize and balance with other management objectives such as timber production, profit, wildlife habitat, biodiversity, water quality, etc.
You can design your own field data collector and cloud data storage system. In the cloud, you can define a field data collection task including tables, points, lines, polygons, photos, videos and assign the task to a number of field people. The field people can start the applications, login and start the field data collection work. Many field people can work with the same task and all data can be stored in your mobile devices and the cloud database when the internet connection is available.
Unlike other Artificial Intelligence (AI) technologies, our AI technologies are developed to generate strategies to achieve a big number of objectives with millions of variables and constraints. The secrets of our AI technologies are able to find near optimum solutions within a limited time and calculating resources in the huge search space. Our AI technologies are used to solve optimization problems that traditional mathematic methods cannot solve.
EasyCloud is a high performance computing framework. The idea behind EasyCloud is to build a HPC computing cluster using spare computers in the cloud or the private network whenever you need at any places with low cost. The low performance computers work together and become a high performance computing cluster. The objective of developing EasyCloud is to meet the Artificial Intelligence iterative calculation needs and reduce the software development difficulties. For most distributed computing, you can divide a big task into several smaller tasks and send each task into a machine, wait and summarize the results. The machines do not need frequent communication. However some AI iterative calculation applications need frequent communications between machines.
Instead of spending a lot of time and energy to predict how the trees and stands are growing, we use a simple tree and stand growth & yield model and use the field data to adjust our predictions. The big data ideas make forest analysis and planning work a lot of easier, more efficient and more cost effective.
We have developed an integrated Demand and Supply system (aiTree) that can be used for any kinds of Demand and Supply system problems. We have Demand model, Inventory model and Optimization model for production and transportations. We use big data technologies to predict the market demands of each products, and guide the inventory model and the production model.