Smart Farming in Thailand Thailandxe2x80x99s economic growth depends on agriculture. Roughly 30 to 40 percents of the total employment in Thailand is in the agricultural sector, but this group of people do not earn enough to spend on a daily basis. In this study, we proposed two production functions for Thai agriculture: with and without entrepreneurships. Entrepreneurship in agriculture is defined based on Schumpeter framework. In the first model, the Cobb Douglas production function is applied to agricultural production without entrepreneurship and the stochastic frontier analysis is applied as an estimation technique to estimate the parameters. In the second model, the entrepreneurship variable is part of land, capital and labor inputs. Maximum likelihood estimation is used to find the estimated parameters. The results show that the returns to scale obtained from the developed production function with entrepreneurship are greater than those obtained from the production function without entrepreneurship.

Interactive Cultivation System for the Future IoTBased Agriculture As initiatives to increase Japanu0027s declining food selfsufficiency rate and revitalize the field of agriculture, the concept of smart agriculture and urban agriculture are currently being implemented. Automation via Artificial Intelligence is expected to overcome the labor shortage in the agricultural industry. However, the number of skilled farmers who can contribute to gathering crop growth data required for machine learning is restricted, and these data are also limited to localand environmentalbased conditions. In this paper, we propose a system for obtaining composite growth data in various environments and crops targeted for home gardens and paddy fields. An interactive cultivation sensing system consisting of IoTbased technologies is designed and realized to ensure the continuous growth of crops in optimum conditions daily. With this, progress will be made in determining the efficient cultivation conditions for machine learning, and in finding solutions to future problems of agriculture.