Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., thermometers, irradiance sensors, and soil moisture sensors) is installed in the APV system. This study aims at introducing a simulation-based decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and simulation-based performance estimation. Particularly, an agent-based simulation (ABS) is used to mimic functions of an APV system so that a data-driven function and digital twin environment are implemented in the proposed system. The ABS model is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the digital twin technology in the field of agriculture.

Purpose - This article’s aim is to examine how the utilization of existing and future decision-support systems will lead to a change in the auditing process. Research design, data, and methodology - An information system is a special decision-support system that combines information obtained from various sources and communicates among them to help in assessing appropriate complex financial decisions. This paper analyzes techniques such as data and text mining as components of decision-support systems to be used in the auditing process. Results - We present views about how existing decision-support systems will lead to a change in audits. Auditors, who currently collect significant data manually, will in the future move towards management through complex decision-support systems. Conclusions - Although some internal audit functions are integrated into systems of continuous monitoring, the use of such systems remains limited. Thus, instead of multiple decision-support systems, a unified decision-support system can be deployed for this that includes sensors integrated within a company in different contexts (e.g., production, sales, and accounting) that continually monitors violations of controls, unusual patterns, and unusual transactions.

본 논문에서는 시스템다이내믹스(System Dynamics, SD) 방법론에 입각하여 상수도 시스템의 운영에 내재된 피드백 루프 메커니즘(feedback loop mechanism)을 상수관로의 유지관리와 연관하여 규명하고, 관로 상태의 변화가 전체 시스템에 미치는 영향을포함한 상수도 시스템의 운영지표를예측하여 상수도 시스템의 효율적인운영 및 유지관리를 지원할 수 있는 SD 컴퓨터 모의 모형(simulation model)을 개발하였다. 개발된 모형은