Context-aware Dynamic Discovery and Configuration of 'Things' in Smart Environments

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as RFIDs, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Currently, such Internet-connected objects or `things' outnumber both people and computers connected to the Internet and their population is expected to grow to 50 billion in the next 5 to 10 years. To be able to develop IoT applications, such `things' must become dynamically integrated into emerging information networks supported by architecturally scalable and economically feasible Internet service delivery models, such as cloud computing. Achieving such integration through discovery and configuration of `things' is a challenging task. Towards this end, we propose a Context-Aware Dynamic Discovery of {Things} (CADDOT) model. We have developed a tool SmartLink, that is capable of discovering sensors deployed in a particular location despite their heterogeneity. SmartLink helps to establish the direct communication between sensor hardware and cloud-based IoT middleware platforms. We address the challenge of heterogeneity using a plug in architecture. Our prototype tool is developed on an Android platform. Further, we employ the Global Sensor Network (GSN) as the IoT middleware for the proof of concept validation. The significance of the proposed solution is validated using a test-bed that comprises 52 Arduino-based Libelium sensors.Comment: Big Data and Internet of Things: A Roadmap for Smart Environments, Studies in Computational Intelligence book series, Springer Berlin Heidelberg, 201

Sensor Search Techniques for Sensing as a Service Architecture for The Internet of Things

The Internet of Things (IoT) is part of the Internet of the future and will comprise billions of intelligent communicating "things" or Internet Connected Objects (ICO) which will have sensing, actuating, and data processing capabilities. Each ICO will have one or more embedded sensors that will capture potentially enormous amounts of data. The sensors and related data streams can be clustered physically or virtually, which raises the challenge of searching and selecting the right sensors for a query in an efficient and effective way. This paper proposes a context-aware sensor search, selection and ranking model, called CASSARAM, to address the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. CASSARAM takes into account user preferences and considers a broad range of sensor characteristics, such as reliability, accuracy, location, battery life, and many more. The paper highlights the importance of sensor search, selection and ranking for the IoT, identifies important characteristics of both sensors and data capture processes, and discusses how semantic and quantitative reasoning can be combined together. This work also addresses challenges such as efficient distributed sensor search and relational-expression based filtering. CASSARAM testing and performance evaluation results are presented and discussed.Comment: IEEE sensors Journal, 2013. arXiv admin note: text overlap with arXiv:1303.244

Semantic Gateway as a Service architecture for IoT Interoperability

The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into vertical silos of proprietary systems, providing little or no interoperability with similar systems. As the IoT represents future state of the Internet, an intelligent and scalable architecture is required to provide connectivity between these silos, enabling discovery of physical sensors and interpretation of messages between things. This paper proposes a gateway and Semantic Web enabled IoT architecture to provide interoperability between systems using established communication and data standards. The Semantic Gateway as Service (SGS) allows translation between messaging protocols such as XMPP, CoAP and MQTT via a multi-protocol proxy architecture. Utilization of broadly accepted specifications such as W3C's Semantic Sensor Network (SSN) ontology for semantic annotations of sensor data provide semantic interoperability between messages and support semantic reasoning to obtain higher-level actionable knowledge from low-level sensor data.Comment: 16 page

Greenhouse Monitoring and Automation Using Arduino: a Review on Precision Farming and Internet of Things (IoT)

The 21st century became the beginning of the development of information technology, where one of the revolutions was the presence of the Internet of Things. Internet of Things or abbreviated as IoT is a technology that combines electronic devices, sensors, and the internet to manage data and applications. The Internet of Things can be adopted in agriculture for crop management as a media for monitoring and controlling, especially in greenhouses and is called Precision Farming. The application of precision farming will be more effective in a greenhouse because it is easier to engineer similar environmental conditions. IoT development in greenhouses is using Arduino Microcontroller or Raspberry Pi Microcomputer. These devices are used because the price is low and easy to get on the market and can be designed so that technicians who have limited information technology knowledge can run it. To be able to manage greenhouses with IoT requires sensors as five senses that can detect changes that occur in the greenhouse. By using sensors, the hardware can detect what is happening in the greenhouse and make decisions based on the data acquired. Some sensors that are often used in Precision Farming are temperature and humidity sensors, soil moisture sensors, and light sensors. In the Internet of Things, the data that has been acquired by the hardware will then be transmitted wirelessly. The wireless connections used are Bluetooth, ZigBee Protocol, and Wi-Fi, where Bluetooth and Zigbee connections have a short distance between 10 - 100 meters, while Wi-Fi has a longer distance especially when connected to the Internet. The purpose of this paper is to understand the advantages and challenges of adopting IoT-based Precision Farming for monitoring and automation

A Business Perspective on Internet of Things

Sensors are rapidly being integrated everywhere, in every aspect of our lives, ranging from home automation to wearable sensors for pervasive healthcare management. We hear ubiquitously for ubiquitous devices. In recent years, increasingly we are listening and talking about phrases like “Internet of Things”, “M2M”, “Context awareness”, “Web of Things”, which announce the new era to come, where we will be surrounded with smart devices, which communicate with each other to easer and beautify our lives. This article reports on our findings about the business perspective on internet of things. It involves literature review on the internet of things world and its impact in the business domain. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

A secure lightweight authentication mechanism for IoT devices in generic domain

The Internet of Things prompt deployment enhances the security concerns of these systems in recent years. The enormous exchange of sensory information between devices raises the necessity for a secure authentication scheme for Internet of Things devices. Despite many proposed schemes, providing authenticated and secure communication for Internet of Things devices is still an open issue. This research addresses challenges pertaining to the Internet of Things authentication, verification, and communication, and proposes a new secure lightweight mechanism for Internet of Things devices in the generic domain. The proposed authentication method utilizes environmental variables obtained by sensors to allow the system to identify genuine devices and reject anomalous connections