# Smart Sensors and Smart Data for Precision Agriculture: A Review
###### Abstract  
Precision agriculture, driven by the convergence of smart sensors and advanced technologies, has emerged as a transformative force in modern farming practices. The present review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture. The main focus is on the integration of smart sensors, coupled with technologies such as the Internet of Things (IoT), big data analytics, and Artificial Intelligence (AI). This analysis is set in the context of optimizing crop management, using resources wisely, and promoting sustainability in the agricultural sector. This review aims to provide an in-depth understanding of emerging trends and key developments in the field of precision agriculture. By highlighting the benefits of integrating smart sensors and innovative technologies, it aspires to enlighten farming practitioners, researchers, and policymakers on best practices, current challenges, and prospects. It aims to foster a transition towards more sustainable, efficient, and intelligent farming practices while encouraging the continued adoption and adaptation of new technologies. smart sensors; precision agriculture; smart data; optimization and control +
Footnote †: journal: Sensors  
11 March 202416 April 202416 April  
crucial role in addressing various challenges related to PA [28]. Agricultural monitoring systems, powered by Wireless Sensor Networks (WSNs) deployed in cultivated areas, provide monitoring services to maintain optimal plant growth and enable early detection of conditions that could lead to widespread plant diseases [29; 30; 31]. In addition, smart irrigation systems, integrating IoT and sensor technology, are emerging as a solution to address the scarcity of clean water resources required by various plant crops, ensuring optimal use of water resources in PA [32; 33]. Meeting the challenge of adapting platforms to the requirements of soilless cultivation in smart greenhouses, particularly in the context of moderate saline water use, is a key aspect of PA [34]. This challenge is effectively met by integrating IoT, cloud computing, and edge computing technologies. Figure 1 shows an architecture diagram for smart greenhouse applications in precision agriculture. The literature review reveals an extensive range of techniques and tools used by researchers in PA using WSNs. Various platforms, such as Arduino, IMOTE2, MICAZ, MOSEK, the MDA300 sensor board, EZ430-RF2500, Indriya, MSP430, PIC16F877, ZKOS, MDA320, the CVX toolbox, MTS400, and the Veris mobile sensor platform, have been developed to integrate various sensors for the collection of crucial data information relating to PA parameters [35]. In particular, the Arduino platform has become a popular choice due to its affordability and ease of integration [36]. In addition, researchers have developed algorithms such as DCTA (Dynamic Converge cast Tree Algorithm) [37], OASNDFA (Optimized Algorithm of Sensor Node Deployment for intelligent Agricultural monitoring) [38], BOP (Beacon Only Period) [39], distributed localization algorithms [40], polynomial-time algorithms for node deployment [41], range-based localization algorithms [42], electromagnetic induction algorithms [43], MLR (Multiple Regression Analysis) [44], PCR (Principal Component Regression) [45], and PLSR (Partial Least Squares Regression) [46] methods for efficient monitoring and intelligent irrigation of crops. The review also highlights the introduction of new communication protocols, including the Fuzzy-based Energy Efficiency Protocol [47; 48], APTEEN (Adaptive Periodic Threshold-sensitive Energy Efficient sensor Network protocol) [49; 50], while operating systems such as Tiny OS and Tiny OS2.0 [51] are frequently adopted for sensor implementations in PA [35]. Table 1 shows an example of the platforms available in this context. Figure 1: Smart greenhouse architecture diagram. In this context, this work presents a systematic literature review approach using the Web of Science database for the period 2018-2023.