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The purpose of developing smart environment systems model for optimization in agriculture is to monitor soil, water, pollution levels, and weather conditions in farming. The monitoring process is carried out to increase the level of agricultural productivity. The model can be used to assist farmers in the decision-making process to cultivate the land and determine the types of commodities to be planted. The method used to develop the model is a descriptive qualitative. The result of the research is a model. Poor pollution levels and relatively erratic weather can worsen the productivity of agricultural land. These conditions make it difficult for farmers to determine the right seeds and fertilizers to use, as well as the right time to start the planting period. Thus the model is expected to support farmers in increasing the quantity and quality of their agricultural products. The model is developed as a part of the implementation of the smart city and internet of things (IoT) concepts which specialize in creating smart environments in agriculture.