George Kokkonis

Real-time wireless multisensory smart surveillance with 3D-HEVC streams for internet-of-things (IoT)

This paper presents the design of a novel, real-time, wireless, multisensory, smart surveillance system with 3D-HEVC features. The proposed high-level system architecture of the surveillance system is analyzed. The advantages of HEVC encoding are presented. Methods for synchronization between multiple streams are presented. Available wireless standards are presented and compared. A network-adaptive transmission protocol for a reliable, real-time, multisensory surveillance system is proposed. Adaptive packet frame grouping (APFG) and adaptive quantization are deployed to maximize the quality-of-experience (QoE). Measurements of the proposed protocol have been shown to provide superior results compared to existing transport protocols.

Efficient algorithm for transferring a real-time HEVC stream with haptic data through the internet

It is widely accepted that the growth of Internet and the improvement of Internet’s network conditions helped real-time applications to flourish. The demand for Ultra-High Definition video is constantly increasing. Apart from video and sound, a new kind of real-time data is making its appearance, haptic data. The efficient synchronization of video, audio, and haptic data is a rather challenging effort. The new High-Efficiency Video Coding (HEVC) is quite promising for real-time ultra-high definition video transferring through the Internet. This paper presents related work on High-Efficiency Video Coding. It points out the challenges and the synchronization techniques that have been proposed for synchronizing video and haptic data. Comparative tests between H.264 and HEVC are undertaken. Measurements for the network conditions of the Internet are carried out. The equations for the transferring delay of all the inter-prediction configurations of the HEVC are defined. Finally, it proposes a new efficient algorithm for transferring a real-time HEVC stream with haptic data through the Internet.

Network Adaptive Flow Control Algorithm for Haptic Data Over the Internet–NAFCAH

This paper deals with the transfer of real time haptic data over the Internet. Some interested transport protocols have already been proposed for the transport of real time haptic data. This paper presents the related work on haptic data transferring. A new network adaptive flow control algorithm is proposed. The new algorithm combines most of the known flow control algorithms while taking into account the network conditions οf the Internet and the significant haptic events.

Proposed cloud infrastructure of wearable and ubiquitous medical services

A Wearable Health Monitoring system is described that uses low-cost off the shelf sensors and computing components, along with custom made software, to provide an economical solution to personalized health care monitoring problems, while retaining all the functionality and flexibility of more expensive systems. Cloud technology is used to store sensor measurements which are categorized based on the criticality of bio-signals. Furthermore, a new session protocol for medical sensor data transmission is proposed. In a prototype system, tests based on different transmission architectures have so far yielded useful and favorable results in comparison with existing protocols and usually more expensive systems.

A Survey of Transport Protocols for Haptic Applications

The term Hap tic refers to the sense of touch. The feeling has the ability to increase the sense of reality, to excite the user and improve the quality of experience. To carry out this sense through the Internet was, until recently, impracticable due to processing inefficiencies and/or protocol performance in capabilities, such as throughput and jitter constraints. This paper describes a Hap tic system architecture. Moreover it presents a survey of transport protocols for hap tic applications. It also performs a classification of related protocol capabilities and outlines the flow requirements that should be met by protocols designed to carry such data.

Efficient Large-scale Medical Data (eHealth Big Data) Analytics in Internet of Things

Recent technologies such as Big Data could be used in order to help the improvement of other fields except for the telecommunication field. Due to the Health field, the Big Data technology could contribute with the aim to help for the purpose of analysis and management of the huge amounts of health data. The main objective of this research proposal is an analytical study of the technologies IoT, Cloud Computing (CC) and large-scale data (Big Data) to resolve various issues facing the health sector in relation to these technologies. The purpose of the research proposal is the collection of medical (e-health) big data in real time. The collection will be performed by sensor devices and actuators, which will wear patients who suffer from various ailments. Then is following, the transfer of these data through a network to a cloud server. Additionally, these data will be processed in the cloud which makes its analysis so as to become meaningless. By the analysis of these data is done the data mining. Finally, to address the various problems in the health sector, the transfer of the analyzed health data will be held by the devices of the relevant persons. Also, in our study, we will deal with the security of medical data which constitute personal data and must be protected.

Evaluating transport and application layer protocols for haptic applications

Recently, a number of transport and application layer protocols for haptic and Interactive applications have been proposed. This paper presents a survey of the above protocols. It outlines the haptic data transmission characteristics. It also depicts the qualitative features that transport and application layer protocols should contain in order to carry haptic data. Based on these criteria, evaluation of the above protocols is performed.

A Smart IoT Fuzzy Irrigation System

This paper proposes a novel fuzzy computational algorithm for IoT smart irrigation systems. It describes all the possible sensors, actuators and microcontrollers that could be used in the irrigation systems. Based on these sensors a novel system architecture is presented. The irrigation system continuously monitoring air temperature and humidity, and ground moisture. The ground humidity sensors are interspersed all over the field. The measurements are send in a microcontroller that applies a fuzzy computational algorithm and decides whether to open a servo valve or not. All the data collected from the microcontroller are sent to a cloud database for statistical information and processing.

A novel microclimate forecasting system architecture integrating GPS measurements and meteorological-sensor data

It is apparent that local climatic conditions have clear implications for agriculture. For this reason accurate information on local climate dynamics is essential for agricultural planning. This study introduces a methodology that aims to enhance microclimate monitoring through GPS networks. This paper describes this novel approach, its implications and presents some preliminary results. Authors propose a novel implementation of a weather monitoring system comprised of existing geodetic and meteorological sensors cooperative efforts, coordinated by roaming microclimate sensors. Such system shall be utilized for the real-time prediction of crucial and emergent phenomena for the agricultural industry. This system shall offer more accurate predictions with the use of spatial microclimate profiles and water vapor content estimates attained from GPS measures. Furthermore, a new session protocol based on SNMP protocol shall be used for data acquisition and a caster station for post processing and visualization purposes.

Snmp for Ethernet Networks SETH: A Network Benchmark Toolkit for Managing Routers Statistical Information

In this paper authors present a new open source SNMP manager application called SETH. This application includes the following major attributes over existing management tools: MIB file parsing capabilities, automatic discovery of network topology and variable up to real-time probing frequency of network equipment in order to extract useful statistical information regarding network conditions. Network information is acquired from network devices using real-time SNMP probes close to agent systems clock granularity. Then re-configurable network metrics are calculated and visualized. Additionally, SNMP trap or notification messages send by routers, indicating cases of network emergencies, are also recorded. Graphical visualization of metric values, network correlation functions and support for all SNMP protocol versions is also provided by the tool.