Advancements and challenges in agriculture: a comprehensive review of machine learning and IoT applications in vertical farming and controlled environment agriculture

Farming is not easy to approach things, as we must feed approximately 8 million people daily. Traditional farming is an old-fashioned technique that takes so much time to produce. Due to this, we need some modern technology to increase our production. But research has shown that in 50 years, there will be 8.3 billion more people on Earth than there are now. It will need an extra 109 hectares of cropland, which doesn't already exist, to feed these new immigrants. There are also clear signs that pollution and the rise in population are worsening. Despite the benefits of smart traditional farming, there are a number of drawbacks to traditional farming. Regardless of soil pollution, water pollution, land pollution, energy loss, climatic conditions, electricity waste, and transportation costs, another option will be better for the food production industry. According to the research, to feed 8 billion people, we would need an additional 109 hectares of land. That is the typical problem that the farmers will face because most of the hollandaise nowadays. So, using this building concept, we will implement indoor farming, which means planting fruits and vegetables inside the tall building, an advanced form of a greenhouse. The innovative idea, also known as Vertical Farming (VF), integrates agricultural design with building design in a tall structure inside of cities. Implementing VF will solve many challenges by utilizing modern machine learning, IoT, and AI techniques, increasing VF productivity and quality. In VF, aeroponics consumes 98% less water than conventional farming. Human health, comfort, and productivity directly correlate with the indoor climate. Systems for vertical plant walls with sensors and actuators have become a good way to control the environment inside a building. They are using a set-up of vertical plant walls with anomaly detection techniques based on machine learning to increase automation and intelligence for predictive indoor climate maintenance.

Advancements and challenges in agriculture: a comprehensive review of machine learning and IoT applications in vertical farming and controlled environment agriculture Keywords:

Drawbacks of traditional farming , Vertical farming , Sensors and actuators , Anomaly Detection , Predictive indoor climate maintenance