Google’s Android Based Brillo Has the Potential to Take IoT Automation to Next Level

brillo1 300x155 Google’s Android Based Brillo Has the Potential to Take IoT Automation to Next LevelWith the acquisition of Nest last year, Google has demonstrated its interest in the field of smart home. At recently concluded Google I/O annual developer conference, the group of Mountain View celebrates a further step forward, talking openly about the Internet of Things.

Born Brillo, a project to connect any device used, not only smartphones, tablets, computers and smartwatch, but also those that are part of everyday life such as home appliances, cars, surveillance systems etc.

Brillo is the ecosystem through which Google intends to play a leading role in the IoT. It is a platform derived from Android, and reduced to essentials to be performed on devices with minimum system requirements, therefore, suitable to be fitted for example in lamps for smart intelligently manage the lighting system of the house. The strength of Brillo is the ability to recognize these devices in an entirely automatic way in smartphones and tablets, as well as simplify the configuration process, making it accessible even to beginners.

It will be able to connect devices of all kinds, through the use of sensors from the extremely low power consumption, enabling them to communicate with each other and enabling users to interact with it such as centralized refrigerators, equipment for monitoring of home, lighting and much more talking to each other.

In addition to home automation, Brillo is also designed for industrial use. Thus, a plant could, for example, use it to connect its sensors and manufacturing equipment.

Google’s another project Weave will be used as the cross-platform protocol, based on JSON (JavaScript Object Notation), through which developers can put in communication between their devices and objects compatible with Brillo, thereby taking advantage of the enormous potential of synchronization of cloud platforms and Mobile application versatility.

As regards the technical specifications, it seems that the software developed by Google can run on devices with a small quantity of RAM, even if only 32 or 64 MB. It supports Wi-Fi connectivity and Bluetooth low energy, does not require particularly powerful processors to run and the Thread protocol used by equipment designed by Nest, a Google property company specializing in intelligent thermal control systems.

Google Brillo IoT is based on a kernel that is derivative of the Android system; naturally it compact the bone to be unified with devices of very small size and devices not too capable on the hardware side. Given the market share of Android and the open source nature, Brillo has the potential to reach the same level as Android. The choice of keeping popular Android mobile OS caters especially to the simplification of procedures developed by device manufacturers.

One thing is sure – one linked to the Internet of Things is a new territory, but which have already staked their eyes for all big technology industries. Microsoft recently announced the arrival of a specially developed IoT version of the Window 10 operating system. Huawei has presented an IoT platform called LiteOS weighing just 10 kB and Samsung has already launched the chip design intended specifically for this sector.

The IoT will come soon in our lives every day without making too much noise with a number of interconnected devices that will grow dramatically in the coming years, and it is obvious that all the big names are getting ready to new market requirements.


IBM Lays Industry Specific Powerful Behavior Based Predictive Analytics

predictive analytics predictive models 300x183 IBM Lays Industry Specific Powerful Behavior Based Predictive Analytics

Image source IBM

The challenge for organizations is to capture, manage and make sense of their data in real time so that many employees can make better decisions faster. In the course of time, predictive analytics evolve and becomes accessible to all enterprise users, regardless of their industry.

IBM is trying to position the company as the leader in predictive analysis and announced a new set of 20 new predictive analytic solutions unique to each industry. Using the new IBM applications, companies can get quick answers to questions such as how many different color combinations fabrics should we continue to sell in our stores? People who spend time at the table after 20:00 are they more likely to be exposed or late to repay their bank loans? When should we stop the production of an oil well to pump maintenance?

The new generation of IBM solutions can be applied to several sectors – banking, telecommunications, insurance, automotive, energy and other sectors. At the heart of these solutions is a set of data preparation tools for the integration of specific data sources for industry such as pre-built models and predictive analysis of its own, and tables interactive and specific board to help business users to share findings between teams and organizations.

IBM says, “the new solutions draw on company’s vast industry and analytics expertise from over 50,000 client engagements. Each solution includes pre-built predictive analytic modeling patterns and interfaces for focused industry use cases, as well as data preparation capabilities to manage unique data and streamline the collection and preparation of data for analytics. With interactive and role-specific dashboards, business users can share predictive insights across teams and organizations that can give them a deeper understanding of their customers, assets and operations to help them make better decisions and act with greater speed and fewer resources.”

In the area of Banking, the AML Monitoring and Analytics for Financial Services, the Multi-Channel Fraud Analytics and Behavior-based Customer Insight operate, respectively, in terms of mitigating money laundering risks, prevention of financial fraud and customization customer experience.

The Asset Analytics for Rotational Equipment is designed by IBM solutions for the chemical and oil industry and uses the predictive analysis to anticipate operational breaks and enhance the reliability and availability of critical equipment.

In the financial segment, Regulatory Compliance and Control and Trade Compliance Analytics enable better risk management and regulatory compliance and comprehensive view of the market, using analytical capacity.

In the area of consumer products, the technology company has created a solution that you want to study the customers’ consumption behavior and their reactions to certain marketing strategies. The Social Merchandising allows enhancing the operational efficiency of companies that wish to reach a particular group of consumers.

In the sphere of insurance, the IBM Analytics Solution Insurance gives a greater customer experience and reduce the dropout rate, the Producer Life Cycle and Credential Management help insurers automate processes, and the Property & Casualty Claims Fraud enables a more efficient identification and needs of fraud incidents.

For the media and entertainment area players, IBM developed the Behavior-based Audience Insight to a better understanding of their audiences and more efficiently create advertising and marketing campaigns and new content.

In April, following in the footsteps of its closest competitor Microsoft, Amazon announced the Amazon Machine Learning, a fully managed cloud service designed to draw useful information from mountains of data that it is sometimes difficult to exploit, for reasons of complexity, time or energy.


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