The Life Intelligence and Office Information System (LOIS) Technical Committee of the Institute of Electronics, Information and Communication Engineers (IEICE) dates its origin to May 1986. This Technical Committee (TC) has covered the research fields of the office related systems for more than 30 years. Over this time, this TC, under its multiple name changes, has served as a forum for research and provided many opportunities for not only office users but also ordinary users of systems and services to present ideas and discussions. Therefore, these advanced technologies have been diffused from big enterprises to small companies and home users responsible for their management and operation. This paper sums up the technology trends and views of the office related systems and services covered in the 30 years of presentations of the LOIS Technical Committees by using the new literature analysis system based on the IEICE Knowledge Discovery system (I-Scover system).

This paper describes a future private network service and the system configurations for providing it. Technologies and service trends in local area and wide area networks are shown. As network services become more diversified and integrated, it becomes more difficult for users to use the networks effectively. This paper shows how this problem can be solved by using virtual network technology to attain seamless networking. It also presents the concept of group networking among many parties, which can be used as the basis for a virtual private network.

The Cyber-Physical Integrated Society (CPIS) is being formed with the fusion of cyber-space and the real-world. In this paper, we will discuss Data-Driven Decision-Making (DDDM) support systems to solve social problems in the CPIS. First, we introduce a Web of Resources (WoR) that uses Web booking log data for destination data management. Next, we introduce an Internet of Persons (IoP) system to visualize individual and group flows of people by analyzing collected Wi-Fi usage log data. Specifically, we present examples of how WoR and IoP visualize flows of groups of people that can be shared across different industries, including telecommunications carriers and railway operators, and policy decision support for local, short-term events. Finally, the importance of data-driven training of human resources to support DDDM in the future CPIS is discussed.