In 2011 Ericsson and Cisco estimated 50 billion Internet connected devices by 2020, encouraged by this industry is developing application frameworks to scale the Internet of Things. This paper presents a survey of commercial frameworks and platforms designed for developing and running Internet of Things applications. The survey covers frameworks supported by big players in the software and electronics industries. The frameworks are evaluated against criteria such as architectural approach, industry support, standards based protocols and interoperability, security, hardware requirements, governance and support for rapid application development. There is a multitude of frameworks available and here a total 17 frameworks and platforms are considered. The intention of this paper is to present recent developments in commercial IoT frameworks and furthermore, identify trends in the current design of frameworks for the Internet of Things; enabling massively connected cyber physical systems.

Increasing the efficiency of production and manufacturing processes is a key goal of initiatives like Industry 4.0. Within the context of the European research project ARROWHEAD, we enable and secure smart maintenance services. An overall goal is to proactively predict and optimize the Maintenance, Repair and Operations (MRO) processes carried out by a device maintainer, for industrial devices deployed at the customer. Therefore it is necessary to centrally acquire maintenance relevant equipment status data from remotely located devices over the Internet. Consequently, security and privacy issues arise from connecting devices to the Internet, and sending data from customer sites to the maintainer's back-end. In this paper we consider an exemplary automotive use case with an AVL Particle Counter (APC) as device. The APC transmits its status information by means of a fingerprint via the publish-subscribe protocol Message Queue Telemetry Transport (MQTT) to an MQTT Information Broker in the remotely located AVL back-end. In a threat analysis we focus on the MQTT routing information asset and identify two elementary security goals in regard to client authentication. Consequently we propose a system architecture incorporating a hardware security controller that processes the Transport Layer Security (TLS) client authentication step. We validate the feasibility of the concept by means of a prototype implementation. Experimental results indicate that no significant performance impact is imposed by the hardware security element. The security evaluation confirms the advanced security of our system, which we believe lays the foundation for security and privacy in future smart service infrastructures.

Video moment retrieval aims to locate the timestamps best matching the query description within an untrimmed video. However, existing video moment retrieval approaches typically suffer from two major limitations: (1)Utilize only negative moment-sentence pairs sampled from intra-videos, which may overfit the bias of the dataset and not have an excellent understanding of the video and query due to the dataset size and annotation biases. (2)Decouple the video and the query, perform unimodal learning separately, and then concatenate them together as multimodal fusion features. In this paper, we propose a novel approach named Momentum Contrastive Matching Network(MCMN). Inspired by MoCo, we propose the Momentum Cross-modal Contrast for cross-modal learning to enable large-scale negative sample interactions, which contributes to the generation of more precise and discriminative representations, and use temporal decay to model key attenuation in the memory queue when computing the contrastive loss. In addition, we use an attention module to adaptively generate clip-specific word embeddings to achieve semantic alignment from a temporal perspective, which are considered to be more important for finding relevant video contents with large boundary ambiguities. Experimental results on the three major video moment retrieval benchmark datasets, including TACoS, Charades-STA, and ActivityNet Captions demonstrate that MCMN surpasses previous methods and reaches state-of-the-art with disparate visual features.

Europa has launched multiple initiatives and research projects to remain competitive in a globalized world and keep industry and manufacturing on-shore. Funded by EU and member countries, project ARROWHEAD[1] focuses research and innovation for collaborative automation using interoperable services for smart production, to improve quality, efficiency, flexibility and cost competiveness. This includes an important new aspect called “Smart Services”, which aims to apply SOA (service oriented architecture) to maintenance and service of production systems and its parts, which still carry a huge potential for further gains in cost and energy savings. However, there will be no “big bang”. How can we turn present-day variety of diverse, specialized, and legacy loaded embedded systems into connected, SOA based cooperating participants of the Internet of Things (IoT)? This case study portrays the solution followed in ARROWHEAD WP1.1, for devices used in end-of-line (EoL) test systems in automotive powertrain production.

This work presents, for the first time, a custom-built high frequency (HF) radio frequency identification (RFID) system that enables the communication with an RFID transponder (tag), which is attached to an object located in an enclosed metal housing. Proof of concept measurements of the custom-built HF RFID system show a good system performance and a favorable extension of the read range in the metal environment by 19% in comparison to the read range of the free space system. These results are realized by a novel passive repeater structure, which is included in the system (i.e., reader-repeater-tag). The passive repeater consists of an arrangement of two booster antennas and ferrite material. Next to simulation and measurement results, the work provides an equivalent circuit model of the reader-repeater-tag system for system design.

Wireless Sensor Networks (WSNs) are at the verge of a broad acceptance in demanding industrial applications. Nodes must fulfill key requirements like reliability and deterministic communication, but also energy autarky in order to allow maintenance-free systems. In this paper a system combining low power, robust communication with appropriate methods for energy harvesting and energy management is suggested. By comparing two alternative variants for power-management, constraints of a solar-cell powered node design are derived. The resulting system demonstrates energy sufficiency at standard industrial indoor lighting conditions of 1300 lx for sensor nodes sampling temperature values at 10 Hz and transmitting once per second.