This paper describes a study on the design and implementation of a smart crop harvesting system that applies artificial intelligence (AI) technology to address some of the major challenges facing modern agriculture, particularly labor shortages, aging rural populations, and decreasing rural areas due to over-urbanization. The system developed in this study provides three main functions: real-time monitoring of crop growth status using high-resolution cameras, a machine learning-based harvest timing prediction algorithm, and an automated harvesting mechanism. The system is expected to improve agricultural productivity, realize labor savings, and contribute to sustainable agricultural development.

This study introduces a pioneering monitoring system designed to forecast melon size using the ARIMA (Auto Regressive Integrated Moving Average) model, set against the backdrop of the Fourth Industrial Revolution's integration of advanced technologies into agriculture. The project underscores the escalating role of agtech, driven by the amalgamation of big data, machine learning, drone technology, and computer vision, aimed at enhancing agricultural productivity and meeting the rising food demand. Through the deployment of ARIMA models, this research endeavors to provide melon farmers with precise predictions of fruit size, thereby facilitating better crop management and production planning. In conclusion, this research provides significant insights into the application of ARIMA models for predicting melon size, demonstrating the potential to improve agricultural practices through precision farming. However, the study also acknowledges the limitations posed by the reliance on single-season data and the potential for overfitting, suggesting the need for further research into multivariate time series models and the incorporation of more extensive data sets to refine and enhance the predictive capabilities of the system.

Digital agriculture based on ICT represents an approach that integrates modern technologies into the field of agriculture to enhance productivity and realize sustainable farming practices. Here are some of the key technologies involved in digital agriculture: First, remote sensing and monitoring systems allow real-time observation and data collection on crop conditions. Second, precision agriculture techniques optimize the use of pesticides and fertilizers. Third, the introduction of automated agricultural machinery reduces reliance on manual labor by mechanizing tasks, increasing efficiency. Overall, ICT-based digital agriculture maximizes the efficiency of agricultural practices, contributes to environmental protection, and provides benefits to both consumers and producers, offering a new paradigm in agriculture.

Today, most energy‐intensive processes have a high degree of optimization. However, in some of these processes large amounts of energy are inevitably released due to the way in which this energy is used. One of the most obvious examples is produced in the power plants during the process of obtaining electrical energy through the transformation of some kind of energy (chemical, kinetic, thermal, lighting, and nuclear or solar energy, among others). This released energy can be used in other processes that may need it so that no additional energy is needed. One of the possible uses of this energy is its use in greenhouses. Greenhouses need large amounts of energy to recreate the climatic conditions that crops need, which are not those of the weather station. To take advantage of the energy released from the power stations in greenhouses, a system based on agents has been developed that manages energy and allows it to be reused. This paper explains how the system allows us to reuse energy by a power plant and how the agents that integrate the system by means of communication with sensors and actuators and the use of data analysis algorithms allow us to use this energy in greenhouses, providing a reduction of the energy they need without the system. The system has been tested in several greenhouses with a pepper crop.

Recently, agriculture has developed remarkably. In recent years, the South Korean government has provided a lot of support for smart agriculture. So, South Korean smart farming industry is making a lot of progress lately. Due to the aging population of farmers in the world, governments of developed country are making strenuous efforts to resolve several agricultural problems through smart farming. Farmers also have a lot of interest in smart agriculture, where they can expect to increase their incomes and boost their convenience. In this speech, I want to introduce about the concept of smart farming technology and smart agricultural situation in Korea and following this, I will focus on the status of smart agriculture in major countries, and will attempt to wrap up the lecture by predicting future smart agriculture.

Recently, the research trend and developmental tendency of ubiquitous computing technologies have been heading in the direction which seamlessly provides the optimum service to users through context- awareness, analogy and networking with various sensor nodes. There is an overwhelming need to develop the USN middleware platforms that have the functions for processing data, monitoring, merged communication environments and mutual compatibility with a variety of sensor networks. While research on a base technique in regard to hardware and communication of sensor networks is actively advancing, the middleware technique is still in the early stages. This paper identifies some drawbacks in the previous work. USN middleware was proposed to control application services through context- awareness processing, information collection from sensor networks and design of event-centric architecture.

Wireless communication technology and state-of-the-art miniaturization have enabled the wireless sensor network with smart environmental sensors. The sensor network is a new field which has been vigorously researched in the ubiquitous computing and ad hoc network. How efficiently use the limited energy in this USN (ubiquitous sensor network) has been debated. Utilizing the directed diffusion and gossiping algorithm which is based on the large-scale glass greenhouses, we present a method to prolong the lifespan of the sensor network by transmitting the relevant control packet on an aperiodic basis. In the paper, we present a method to minimize the energy consumption of sensor nodes within glass greenhouses and ensure stable network operation at the same time through energy efficient routing between sensor nodes.

Plenty of new routing protocols have been presented to overcome the difficulty in applying the routing protocol which was proposed for the existing wireless networks (IEEE 802.11) to WSN. Therefore, this paper presents the wired and wireless integrated networks which transmit the information collected from the wireless sensor networks to wired networks via WSN Gateway. At this time, this paper embodies the Zigbee protocol in the wireless networks based on the 802.15.4 standard and designs an advanced routing protocol for wired and wireless integrated networks by modifying the existing ad hoc routing protocol to enable access to wired networks such as the internet. Moreover, we design an integration method which is based on WSN Gateway which integrates two different networks efficiently. To evaluate the proposed research, we simulated an advanced routing method and WSN Gateway in the wired and wireless integrated networks using the NS-2 simulator.