# A Decision Support System for Crop Recommendation Using Machine Learning Classification Algorithms
## 2 Advancements and Techniques Used for Improving Crop Production  
A brief study on the different approaches of decision support systems for predicting crop suitability has been conducted. Many implementations are based on existing crop mineral datasets, satellite image analyses, and real-time data analyses using sensors, Wi-Fi, and drone technologies. Mainly, the recommendation is based on historical crop and soil mineral data. [PERSON] et al. [4] elaborated on the development of the agriculture sector at a large scale in rich countries based on crop and soil parameters. In Kerala, India, to support small and marginal farmers. the soil crop databases collected from cultivation fields and crop calendars were prepared. This was achieved using different electronic devices for the reduction of agricultural expenses. [PERSON] et al. [5] collected soil-weather parameters, such as temperature, humidity, Potential of Hydrogen (pH value), and NPK (Nitrogen, Phosphorus, and Potassium) values using real-time observations over time. The authors used a wireless sensor network and remote server for data collection and analysis and concluded that the performance of the Medium Access Control (MAC) and routing algorithm approach is the best. [PERSON], [PERSON] et al. [6] suggested a model that contains networking and sensors to collect the environmental conditions of fields cultivated with white cabbage crops. It helps the farmer monitor the environmental needs and reduces the losses in farming. [PERSON] et al. [7] performed a brief study on precision agriculture, which can solve food problems and reduce labor costs. The authors explained leads taken in precision farming to handle the day-to-day challenges of pollution and climate change. [PERSON], [PERSON] et al. [8] suggested collecting the leaf temperature and water needs using the sensor. It allows for better farming by identifying the season-wise crop suitability and its needs. The authors discussed Radio Frequency Identification (RFID)-based sensors and EM4325 ultra-high-frequency (UHF) chip utilization in the research. [PERSON] et al. [9] suggested different tools for improving crop production. They applied different tools like Physical Layer Signaling (PLS), Packet Switching (PS), and Connectionless Mode Service (CLS) for crop production. It has been observed that the precision seeding of PLS is better in improving crop production. [PERSON] et al. [10] describe how the Internet of Things (IoT) connects various devices such as mobiles, tablets, and personal computers through machine-to-machine communication. They emphasize that IoT enhances precision agriculture by optimizing the use of resources like pesticides, light, and water, thereby increasing production efficiency and reducing waste. [PERSON] et al. [11] explained the flora test to obtain information about the state of plants, and then they discussed the two different types of data acquisition systems, which depend on portable devices that are helpful in precision agriculture for controlling and monitoring the growth of crops, the usage of water to crops, and managing the pesticides to crops so that farmer can obtain more production using precision agriculture. [PERSON] et al. [12] discuss how traditional agriculture methods are currently used in India and suggest that precision agriculture can replace these methods. Their work indicates that farmers can grow various crops more effectively with precision agriculture. [PERSON] et al. [13] explained that the agriculture field in the Indian agriculture farming industry adapts less innovative technology compared to other industries. In precision agriculture, if we adapt communication and information technologies, which can easily provide less cost-effective methods and can be helpful for smart agriculture, in this work, they prepared a model for agriculture farming that can guide the farmers performing their farming in rural and urban areas so that the production of crop yield increase rapidly, which improves their profits about the farmer's production rate. [PERSON] et al.