The Internet of Things (IoT) envisions that objects may be connected to the Internet, producing and consuming data in real-time. Today, numerous middleware platforms are available to facilitate the communication with these objects. Unfortunately, the interoperability of these platforms is very limited because it requires to "manually" connect the services proposed by each platform. One key design goal for our contribution is not to build yet another middleware, but rather to augment the functionalities of existing systems via an extension to support their integration into a network of heterogeneous IoT hubs. The extension includes a RESTful API to manipulate the basic component of our extension, the IoT feeds. The IoT feeds allow the platform's owner to dynamically marshal the IoT features connected to the platform, as well as the data that they produce. Furthermore, the feeds enable the owner to manage and control the data flows before connecting them to his applications. Subsequently, these feeds may also be published to meta-hubs in order to expose them to third parties. We evaluated an implementation our extension for Android systems to show the feasibility of managing the data flows using the RESTful API on this platform.
The Thing Broker @cite_14 is a centralized platform that provides a Twitter-like abstraction model for things and events to create local ecosystems such as smart homes. All the platforms previously mentioned, apart from OpenIoT, provide a RESTful API to interact with the platform.
@cite_14
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In the Web of Things, standard web technologies and protocols are used to represent and communicate with physical and virtual things. One challenge toward this vision is integrating things with different characteristics, protocols, interfaces and constraints while maintaining the simplicity and flexibility required for a variety of applications. In this paper we present the Thing Broker, a core platform for Web of Things that provides RESTFul interfaces to things using a Twitter-based set of abstractions and communication model. We present the key abstractions, a reference implementation and explain how a typical WoT application can be created using Thing Broker. We finish with a preliminary evaluation and draw some lessons from our experiences. This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing. The decentralized trading market approach, where both autonomous agents and people can consume and produce services expanding own opportunities to reach goals, looks very promising as a part of the Fourth Industrial revolution. The key component of the approach is a blockchain platform that allows an interaction between agents via liability smart contracts. Reliability of a service provider is usually determined by a reputation model. However, this solution only warns future customers about an extent of trust to the service provider in case it could not execute any previous liabilities correctly. From the other hand a blockchain consensus protocol can additionally include a validation procedure that detects incorrect liability executions in order to suspend payment transactions to questionable service providers. The paper presents the validation methodology of a liability execution for agent-based service providers in a decentralized trading market, using the Model Checking method based on the mathematical model of finite state automata and Temporal Logic properties of interest. To demonstrate this concept, we implemented the methodology in the Duckietown application, moving an autonomous mobile robot to achieve a mission goal with the following behavior validation at the end of a completed scenario. We describe a platform for smart, city-wide crowd management based on participatory mobile phone sensing and location situation specific information delivery. The platform supports quick and flexible deployments of end-to-end applications for specific events or spaces that include four key functionalities: (1) Mobile phone based delivery of event space specific information to the users, (2) participatory sensor data collection (from app users) and flexible analysis, (3) location and situation specific message multicast instructing people in different areas to act differently in case of an emergency and (4) post mortem event analysis. This paper describes the requirements that were derived through a series of test deployments, the system architecture, the implementation and the experiences made during real life, large scale deployments. Thus, until today it has been deployed at 14 events in three European countries (UK, Netherlands, Switzerland) and was used by well over 100,000 people.