Think About IOT - Internet Of Things Change your life style.

IoT Week 2013 - The Event on IoT technologies and Innovation and Businesses.Check Out the below Link.

IoT Week 2013 - The Event on IoT technologies and Innovation and Businesses

Source -IOT Week June 16-20 2013

What Is Internet Of Things !!

The Internet of Things - in which ordinary objects get smart and connected, making possible all sorts of new services - promises to give us smarter cities, fewer traffic jams, a cleaner environment and a Series victory for the Cubs. (OK, maybe not that last one.)

Trouble is, while lots of technologists and technophiles talk about the Internet of Things as if it were already here, there really isn't any such thing. Not in any true sense of the term.

To be sure, there are plenty of smart gadgets out there that are wired up and broadcasting data to other devices - home alarms, for instance. Cameras. Heat sensors and hydrometers. But as you might have already noticed, we're still a long way from the day when your refrigerator sees that you're out of milk and orders a new gallon, or when your suitcase checks your calendar for out-of-town meetings and makes sure your travel clothes have been washed and folded. 

Information and analysis

As the new networks link data from products, company assets, or the operating environment, they will generate better information and analysis, which can enhance decision making significantly. Some organizations are starting to deploy these applications in targeted areas, while more radical and demanding uses are still in the conceptual or experimental stages.

1. Tracking behavior

When products are embedded with sensors, companies can track the movements of these products and even monitor interactions with them. Business models can be fine-tuned to take advantage of this behavioral data. Some insurance companies, for example, are offering to install location sensors in customers’ cars. That allows these companies to base the price of policies on how a car is driven as well as where it travels. Pricing can be customized to the actual risks of operating a vehicle rather than based on proxies such as a driver’s age, gender, or place of residence.

2.Enhanced situational awareness

Data from large numbers of sensors, deployed in infrastructure (such as roads and buildings) or to report on environmental conditions (including soil moisture, ocean currents, or weather), can give decision makers a heightened awareness of real-time events, particularly when the sensors are used with advanced display or visualization technologies.

3. Sensor-driven decision analytics

The Internet of Things also can support longer-range, more complex human planning and decision making. The technology requirements—tremendous storage and computing resources linked with advanced software systems that generate a variety of graphical displays for analyzing data—rise accordingly.

In the oil and gas industry, for instance, the next phase of exploration and development could rely on extensive sensor networks placed in the earth’s crust to produce more accurate readings of the location, structure, and dimensions of potential fields than current data-driven methods allow. The payoff: lower development costs and improved oil flows.

What comes next?

The Internet of Things has great promise, yet business, policy, and technical challenges must be tackled before these systems are widely embraced. Early adopters will need to prove that the new sensor-driven business models create superior value. Industry groups and government regulators should study rules on data privacy and data security, particularly for uses that touch on sensitive consumer information. Legal liability frameworks for the bad decisions of automated systems will have to be established by governments, companies, and risk analysts, in consort with insurers. On the technology side, the cost of sensors and actuators must fall to levels that will spark widespread use. Networking technologies and the standards that support them must evolve to the point where data can flow freely among sensors, computers, and actuators. Software to aggregate and analyze data, as well as graphic display techniques, must improve to the point where huge volumes of data can be absorbed by human decision makers or synthesized to guide automated systems more appropriately.

Credit - CNN - Readwrite - MCKinsey.

Next Gen Tech... Social network analysis, Link Analysis, and Visualization

Social network analysis, Link Analysis, and Visualization

• Centrifuge, offers analysts and investigators an integrated suite of capabilities that can help them rapidly understand and glean insight from new data sources.
• IBM SPSS Clementine, data mining suite, includes link visualization software.
• GraphInsight, explore your graphs through high-quality 2D and 3D visualizations.
• Hypersoft OmniContext, helps evaluate communication and collaboration, understand relationships and identify communities and members across geographies, divisions, and internal and external organizations.
• i2 Analyst's Workstation, i2 Inc. software for volume incident analysis; used worldwide to support intelligence-led policing, COMSTAT processes, anti-terrorism/force protection and more.
• InFlow, software for social network analysis & organizational network Analysis.
• KXEN Social Network Analysis (KSN), social network analysis solution for a deeper understanding of customer interactions, the customer connections and communities.
• LPA Data Mining tools let you build Link Analysis based applications like InFlow.
• Maltego, an open source intelligence and forensics application; allows you to identify key relationships and networks. Community Edition available
• marketVisual, online visual relationship mapping.
• NETMAP analytics, innovative combination of link analysis and data visualization, with applications to fraud detection and claims analysis.
• NetMiner, for Exploratory Analysis and Visualization of Network Data.
• Networked Insights: at the intersection of social networking, collective intelligence, and search, Networked Insights discovers customers' needs as they happen.
• NetworkX, a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
• NodeXL, a free, open-source template for Microsoft Excel 2007 and 2010 that makes it easy to explore network graphs.
• OmniAnalyser contains instrumentation for automatic discovery and historic statistical analysis of corporate social networks with accent on different organizational units (users, departments, offices, countries etc.) and graphical data correlation viewing.
• PolyAnalyst, includes software for link analysis and visualization.
• Sentinel Visualizer, with the capabilities of advanced Social Network Analysis, providing the ability to see and analyze complex relationships that exist within data.
• Sonamine, performs scalable customized scoring of massive social networks and graphs.
• Svivot, offers fraud-detection solution based on analysis of networks of people and organizations.
• VisuaLinks(TM) suite, link analysis and data visualization tool
• UCINET, a package for social network analysis.
• Xanalys Link Explorer, provides powerful network analysis tools including link chart and timeline analysis, Bing mapping and Excel integration.

Sites for Social Network Analysis

• INSNA is the professional association for researchers interested in social network analysis.
• SNAP, Stanford social network analysis site, with software, datasets, papers, and more.
• Social network analysis software, wikipedia entry
• Web Identity Search Tool (WIST), for investigating data on Facebook, including finding the degrees of separation between two users.

Free and Open-source Social Network Analysis Software

• GraphChi can run very large graph computations on just a single machine, by using a novel algorithm for processing the graph from disk (SSD or hard drive).
• Graphviz, open source graph visualization software.
• JUNG, the Java Universal Network/Graph Framework, a software library for the modeling, analysis, and visualization of network data.
• libsna, Python open-source library for Social Network Analysis.
• Maltego Community Edition, an open source intelligence and forensics application; allows you to identify key relationships and networks. Commercial edition available.
• NETINF, infers a who-copies-from-whom or who-repeats-after-whom network of news media sites and blogs using the MemeTracker dataset.
• Network Workbench: a large-scale network analysis, modeling and visualization toolkit for biomedical, social science and physics Research.
• Networkx, Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
• Pajek, program for Large Network Analysis.
• R, includes several packages relevant for social network analysis:igraph: generic network analysis package; sna: for sociometric analysis of networks; network manipulates and displays network objects.
• Social Networks Visualiser (SocNetV), a flexible and user-friendly tool for the analysis and visualisation of Social Networks.
• Subdue, graph-based knowledge discovery system that finds structural, relational patterns in data representing entities and relationships.
• sna: R Tools for Social Network Analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, and more.
• statnet, a suite of R packages for social network analysis, simulation and visualization.
• Tulip, an information visualization framework dedicated to the analysis and visualization of relational data (free).

Credit - KD N.