Adaptive end-to-end optimization of mobile video streaming using QoS negotiation

Video streaming over wireless links is a non-trivial problem due to the large and frequent changes in the quality of the underlying radio channel combined with latency constraints. We believe that every layer in a mobile system must be prepared to adapt its behavior to its environment. Thus layers must be capable of operating in multiple modes; each mode will show a different quality and resource usage. Selecting the right mode of operation requires exchange of information between interacting layers. For example, selecting the best channel coding requires information about the quality of the channel (capacity, bit-error-rate) as well as the requirements (latency, reliability) of the compressed video stream generated by the source encoder. In this paper we study the application of our generic QoS negotiation scheme to a specific configuration for mobile video transmission. We describe the results of experiments studying the overall effectiveness, stability, and dynamics of adaptation of our distributed optimization approach

Future internet enablers for VGI applications

This paper presents the authors experiences with the development of mobile Volunteered Geographic Information (VGI) applications in the context of the ENVIROFI project and Future Internet Public Private Partnership (FI-PPP) FP7 research programme.FI-PPP has an ambitious goal of developing a set of Generic FI Enablers (GEs) - software and hardware tools that will simplify development of thematic future internet applications. Our role in the programme was to provide requirements and assess the usability of the GEs from the point of view of the environmental usage area, In addition, we specified and developed three proof of concept implementations of environmental FI applications, and a set of specific environmental enablers (SEs) complementing the functionality offered by GEs. Rather than trying to rebuild the whole infrastructure of the Environmental Information Space (EIS), we concentrated on two aspects: (1) how to assure the existing and future EIS services and applications can be integrated and reused in FI context; and (2) how to profit from the GEs in future environmental applications.This paper concentrates on the GEs and SEs which were used in two of the ENVIROFI pilots which are representative for the emerging class of Volunteered Geographic Information (VGI) use-cases: one of them is pertinent to biodiversity and another to influence of weather and airborne pollution on users’ wellbeing. In VGI applications, the EIS and SensorWeb overlap with the Social web and potentially huge amounts of information from mobile citizens needs to be assessed and fused with the observations from official sources. On the whole, the authors are confident that the FI-PPP programme will greatly influence the EIS, but the paper also warns of the shortcomings in the current GE implementations and provides recommendations for further developments

Mapping the OGC sensor things API onto the OpenIoT middleware

The OGC SensorThings API is an OGC candidate standard for providing an open and unified way to interconnect IoT devices, data, and applications over the Web. The OpenIoT middleware, developed in the OpenIoT project, is an Open Source reference implementation to support IoT applications. Consequently the OpenIoT middleware is the perfect platform to implement the OGC candidate standard and to test its applicability. This paper describes the approach to map the OGC data model to the OpenIoT data model and discusses the findings of this proof of concept experiment

Einfach mächtig - OGC SensorThings API: Sensordaten im Internet der Dinge

Das Thermostat misst die Temperatur, das Smart Meter den Stromverbrauch - alle Dinge werden smarter und haben Sensoren, die die Welt um uns herum beobachten. Aber wie kommt man an all diese Daten heran? Nahezu jede IoT-Plattform hat ihre eigene Schnittstelle und alle funktionieren sie anders. Das Open Geospatial Consortium hat jetzt einen Standard für das Verwalten und Abfragen von Sensordaten entwickelt: Das SensorThings API

Using crowdsource information for managing climate events through the use of modern mobile technology: Paper presented at 2nd International Conference on Citizen Observatories for natural hazards and Water Management, COWM 2018, Venice, 27-30 November 2018

- We propose a mobile application facilitating an ontology to support all participants of a climate-related crises. - Semantic classification is achieved by involving the user and without requiring semantic analysis tools. - Participants in the field can share and exchange information with the control centre. - Using multimodal input and potent analysis modules enhance situational awareness. - Additional crowdsourcing based on ontological backend offers machine-interpretable dat

Management of Sensor Data with Open Standards

In an emergency, getting up-to-date information about the current situation is crucial to orchestrate an efficient response. Due to its objectivity, preciseness and comparability, time-series data offer broad possibilities to manage emergency incidents. Since the Internet of Things (IoT) is rapidly growing with an estimated number of 30 billion sensors in 2020, it offers excellent potential to collect time-series data for improving situational awareness. The IoT brings several challenges: caused by a splintered sensor manufacturer landscape, data comes in various structures, incompatible protocols and unclear semantics. To tackle these challenges a well-defined interface, from where uniform data can be queried, is necessary. The Open Geospatial Consortium (OGC) has recognized this demand and developed the Sensor Things API standard, an open, unified way to interconnect devices throughout the IoT, which is implemented by the FRaunhofer-Open source-SensorThings-Server (FROST). This paper presents the standard, its implementation and the application to the domain of crisis management

An Environmental Sensor Data Suite Using the OGC SensorThings API

In many application domains sensor data contributes an important part to the situation awareness required for decision making. Examples range from environmental and climate change situations to industrial production processes. All these fields need to aggregate and fuse many data sources, the semantics of the data needs to be understood and the results must be presented to the decision makers in an accessible way. This process is already defined as the “sensor to decision chain” [11] but which solutions and technologies can be proposed for implementing it?Since the Internet of Things (IoT) is rapidly growing with an estimated number of 30 billion sensors in 2020, it offers excellent potential to collect time-series data for improving situational awareness. The IoT brings several challenges: caused by a splintered sensor manufacturer landscape, data comes in various structures, incompatible protocols and unclear semantics. To tackle these challenges a well-defined interface, from where uniform data can be queried, is necessary. The Open Geospatial Consortium (OGC) has recognized this demand and developed the SensorThings API (STA) standard, an open, unified way to interconnect devices throughout the IoT. Since its introduction in 2016, it has shown to be a versatile and easy to use standard for exchanging and managing sensor data.This paper proposes the STA as the central part for implementing the sensor to decision chain. Furthermore, it describes several projects that successfully implemented the architecture and identifies open issues with the SensorThings API that, if solved, would further improve the usability of the API

An Environmental Sensor Data Suite Using the OGC SensorThings API

In many application domains sensor data contributes an important part to the situation awareness required for decision making. Examples range from environmental and climate change situations to industrial production processes. All these fields need to aggregate and fuse many data sources, the semantics of the data needs to be understood and the results must be presented to the decision makers in an accessible way. This process is already defined as the “sensor to decision chain” [11] but which solutions and technologies can be proposed for implementing it?Since the Internet of Things (IoT) is rapidly growing with an estimated number of 30 billion sensors in 2020, it offers excellent potential to collect time-series data for improving situational awareness. The IoT brings several challenges: caused by a splintered sensor manufacturer landscape, data comes in various structures, incompatible protocols and unclear semantics. To tackle these challenges a well-defined interface, from where uniform data can be queried, is necessary. The Open Geospatial Consortium (OGC) has recognized this demand and developed the SensorThings API (STA) standard, an open, unified way to interconnect devices throughout the IoT. Since its introduction in 2016, it has shown to be a versatile and easy to use standard for exchanging and managing sensor data.This paper proposes the STA as the central part for implementing the sensor to decision chain. Furthermore, it describes several projects that successfully implemented the architecture and identifies open issues with the SensorThings API that, if solved, would further improve the usability of the API

Future Internet enablers for VGI applications

This paper presents the authors experiences with the development of mobile Volunteered Geographic Information (VGI) applications in the context of the ENVIROFI project and Future Internet Public Private Partnership (FI-PPP) FP7 research programme. FI-PPP has an ambitious goal of developing a set of Generic FI Enablers (GEs) - software and hardware tools that will simplify development of thematic future internet applications. Our role in the programme was to provide requirements and assess the usability of the GEs from the point of view of the environmental usage area, In addition, we specified and developed three proof of concept implementations of environmental FI applications, and a set of specific environmental enablers (SEs) complementing the functionality offered by GEs. Rather than trying to re-build the whole infrastructure of the Environmental Information Space (EIS), we concentrated on two aspects: (1) how to assure the existing and future EIS services and applications can be integrated and reused in FI context; and (2) how to profit from the GEs in future environmental applications. This paper concentrates on the GEs and SEs which were used in two of the ENVIROFI pilots which are representative for the emerging class of Volunteered Geographic Information (VGI) use-cases: one of them is pertinent to biodiversity and another to influence of weather and airborne pollution on users’ wellbeing. In VGI applications, the EIS and SensorWeb overlap with the Social web and potentially huge amounts of information from mobile citizens needs to be assessed and fused with the observations from official sources. On the whole, the authors are confident that the FI-PPP programme will greatly influence the EIS, but the paper also warns of the shortcomings in the current GE implementations and provides recommendations for further developmentsJRC.H.6-Digital Earth and Reference Dat

Extending INSPIRE to the Internet of Things through SensorThings API

Spatial Data Infrastructures (SDI) established during the past two decades “unlocked” heterogeneous geospatial datasets. The European Union INSPIRE Directive laid down the foundation of a pan-European SDI where thousands of public sector data providers make their data, including sensor observations, available for cross-border and cross-domain reuse. At the same time, SDIs should inevitably adopt new technology and standards to remain fit for purpose and address in the best possible way the needs of different stakeholders (government, businesses and citizens). Some of the recurring technical requirements raised by SDI stakeholders include: (i) the need for adoption of RESTful architectures; together with (ii) alternative (to GML) data encodings, such as JavaScript Object Notation (JSON) and binary exchange formats; and (iii) adoption of asynchronous publish–subscribe-based messaging protocols. The newly established OGC standard SensorThings API is particularly interesting to investigate for INSPIRE, as it addresses together all three topics. In this manuscript, we provide our synthesised perspective on the necessary steps for the OGC SensorThings API standard to be considered as a solution that meets the legal obligations stemming out of the INSPIRE Directive. We share our perspective on what should be done concerning: (i) data encoding; and (ii) the use of SensorThings API as a download service