The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability.

An aging population and human longevity is a global trend. Many developed countries are struggling with the yearly increasing healthcare cost that dominantly affects their economy. At the same time, people living with old adults suffering from a progressive brain disorder such as Alzheimer’s disease are enduring even more stress and depression than those patients while caring for them. Accordingly, seniors’ ability to live independently and comfortably in their current home for as long as possible has been crucial to reduce the societal cost for caregiving and thus give family members peace of mind, called ‘aging in place’ (AIP). In this paper we present a way of building AIP services using standard-based IoT platforms and heterogeneous IoT products. An AIP service platform is designed and created by combining previous standard-based IoT platforms in a collaborative way. A service composition tool is also created that allows people to create AIP services in an efficient way. To show practical usability of our proposed system, we choose a service scenario for medication compliance and implement a prototype service which could give old adults medication reminder appropriately at the right time (i.e., when it is time to need to take pills) through light and speaker at home but also wrist band and smartphone even outside the home.

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Recently, interest in financial transactions is increasing, and the number of investors in the stock market is increasing. These investors are applying financial analysis methods to stock trading in order to gain more profits, and combining with artificial intelligence techniques has made it possible to achieve returns in excess of the market average. As a result, the stock trading system based on reinforcement learning has attracted attention, and in recent years, studies are being conducted to optimize financial time series data by Multi-Agent Reinforcement Learning (MARL). However, MARL, which is used in existing stock trading, cannot be fully collaborated because of lack of generalization of experience. Therefore, in this paper, we propose Multi-agent Collaborated Network (MCN) that can share and generalize the experience by agent, and experiment on collaboration in distributed stock trading.

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Vehicular Ad-hoc Network (VANET) is an emerging and very promising technology that has great demand on the access capability of the existing wireless technology. VANETs help improve traffic safety and efficiency. Each vehicle can exchange their information to inform the other vehicles about the current status of the traffic flow or a dangerous situation such as an accident. To achieve these, a reliable and efficient Medium Access Control (MAC) protocol with minimal transmission collisions is required. High speed nodes, absence of infrastructure, variations in topology and their QoS requirements makes it difficult for designing a MAC protocol in vehicular networks. There are several MAC protocols proposed for VANETs to ensure that all the vehicles could send safety messages without collisions by reducing the end-to-end delay and packet loss ratio. This paper gives an overview of the several proposed MAC protocols for VANETs along with their benefits and limitations and presents an overall classification based on their characteristics.

This article suggests a new directed broadcasting method with mobility prediction of moving vehicles in vehicular sensor networks (VSNs). VSNs can play a critical role to ensure prompt delivery of real-time sensing data and be able to prevent various road dangers. The suggested method is particularly for vehicle safety communication (VSC) on highway roads by using directed broadcasting between vehicles. In VSNs, broadcasting is the most suitable communication mechanism for VSC. The simplest broadcasting mechanism is flooding, which introduces the redundant message retransmission and the broadcast storm problem. It is because all vehicles rebroadcast the messages in flooding. The broadcast storm problem can be addressed with selective flooding schemes which select rebroadcast vehicles to perform rebroadcasting. However, selective flooding schemes cannot promise enough reliability for VSC because of the highly dynamic topology and frequent disconnections of vehicular networks. Fast movement and frequent topology changes cause repeated link breakages and it increases the packet loss rate of vehicular networks. In this article, we propose a mobility prediction-based directed broadcasting (MPDB) protocol to achieve a reliable broadcasting in VSNs. MPDB protocol broadcasts emergent messages only to the rear vehicles on the same road. MPDB protocol consists of two phases: (i) mobility prediction phase and (ii) broadcasting phase. The mobility prediction can be acquired through periodical beaconing. In mobility prediction phase, each vehicle gets its rear vehicle set on the same road through neighbour's position, inter-vehicle distance, relative speed and moving direction. In broadcast phase, MPDB protocol selects a vehicle having the largest link available time (LAT) values acquired by the mobility prediction as a rebroadcast vehicle among the rear vehicle set acquired in previous phase. By using LAT for broadcasting propagation, MPDB protocol can intensify the reliability of the message dissemination and also prevent the broadcast storm problem in vehicular networks. The simulation results show that MPDB protocol has better performance improvement in terms of average packet rate and packet delay.

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