# Smart Sensors and Smart Data for Precision Agriculture: A Review
## 2 Types of Smart Sensors in Precision Agriculture
Future improvements may include nano-robotic sensors and predictive capabilities, ultimately making the system independent of human intervention. The application of advanced sensor systems in modern agriculture, particularly in greenhouses, marks a significant technological advance that streamlines agricultural processes. This system [68] uses a wireless sensor network, including the DHT11 humidity and temperature sensor, and an intelligent LoWPAN gateway that connects the Zigbee network to the Internet, enabling continuous data transfer and analysis. The DHT11 sensor excels at measuring temperature and humidity with speed, accuracy, and high resolution, making it a valuable asset in greenhouse environments. The data collected by these sensors is transmitted via the Zigbee network to an intelligent gateway and then sent via mobile data communication to a web service. Intelligent software applications analyze this data, enabling automated responses via actuators to create an optimized microclimate within the greenhouse. This innovative system improves the efficiency of greenhouse farming while promoting higher-quality production at a time when technology is revolutionizing agriculture. The deployment of a ONENET-based remote monitoring and control system for greenhouse environments represents a significant step forward in realizing the potential of the IoT in agriculture. The system presented by [69] features the efficient integration of advanced sensors using the STM32 MCU to monitor air temperature, humidity, light intensity, soil temperature, and moisture in the greenhouse. It integrates a relay control unit and a ONENET IoT cloud platform, enabling remote greenhouse management via computer or mobile devices. In addition to the DHT22 temperature and humidity sensor, the MG811 CO2 concentration sensor, the BH1750 lighting sensor, and the SHT-20X soil temperature and humidity sensor, the information acquisition unit includes the STM32 central controller overseeing data collection and relay control. Data collected by the sensors is processed and relayed to the ONENET cloud platform via the ESP8266 wireless WIFI module, which then connects to the router. This seamless integration enables real-time monitoring and control of greenhouse environmental data, accessible via an intuitive dashboard on the ONENET cloud services platform, optimizing the management of agricultural conditions. Practical results highlight the system's advantages, including high detection accuracy, simple design, and cost-effectiveness. Leveraging cloud-based data storage and real-time monitoring, the system harnesses IoT technology to streamline environmental control in greenhouses, marking a substantial step towards optimizing agricultural practices. This research by [70] highlights the disadvantages of current IoT-based agricultural applications, particularly in terms of their environmental and health implications. To address these concerns, the study introduces Green IoT (G-IoT) and green nanotechnology,aiming to develop a cost-effective, real-time precision agricultural monitoring system. This system aims to minimize energy consumption, reduce Greenhouse Gas (GHG) emissions, and provide a user-friendly interface, enabling farmers to monitor various agricultural parameters such as weather, water, soil, pest detection, intrusion detection, and fire detection remotely via smartphones. Unlike many existing PA monitoring systems that focus solely on irrigation, the proposed system incorporates LoRa technology for long-range communication, reducing energy consumption compared with ZigBee, Wi-Fi, and GSM protocols. The study highlights the importance of periodically monitoring various parameters to inform farmers and avoid wasting resources, thus acting as a decision support system. The integration of G-IoT tools and LoRa technology in the proposed system contributes to its cost-effectiveness, energy efficiency, and accessibility for farmers with no specialist training.