Showing posts from March 20, 2017

The vision of the internet of things

The vision of the internet of things is that, objects of everyday life such as cars, lamps, doors, windows, roadways, pacemakers, wirelessly connected pill-shaped cameras, smart billboards , refrigerators, cattle , to name a few can be equipped with smart sensors that can track useful information about these objects.

The biggest transactions in the internet of things domain yet

Steadily, market players compete to realize the huge economic potential offered by the Internet of Things. Google's $3 billion plus acquisition of Nest, and Qualcomm's $2.5 billion acquisition of CSR are the biggest transactions in this domain yet. I can observe that, Industries are majorly spending on monitoring their supply chain, premises, products and customers. There is a huge wave of variance across the vertical industries when it comes to IoT adoption. According to Research and Markets, Industries like manufacturing, transportation, media & entertainment etc. are having some of the highest IoT Spend as a percentage of their annual revenue.

Here is what the internet of things (IoT) security now signifies

For those who are unfamiliar, security demand in the internet of things (IoT) age surpasses and impacts conventional categories of IT security, physical security and IT/operational technology (OT) security. IoT security now signifies how the various strategies of security must work simultaneously to secure data, protect devices and users, and provide a privacy, transparency and secure experience.

Automated Mapping Technology

For those who are unfamiliar, the automated mapping technology uses artificial intelligence (AI) to quickly create precise, accurate three-dimensional maps. For instance, Mitsubishi Electric’s MMS provides 3D positional information of roads and roadside structures with an absolute precision within 10cm or less, which is collected via a system consisting of laser scanners, cameras and GPS antennas, while driving. Only necessary information, such as road markings and traffic signs, is extracted from laser-point clouds and camera data measured and collected by MMS. Artificial intelligence (AI) improves the precision of extraction and recognition of the only data necessary, resulting in some 10 times faster map creation compared to industry-standard manual creation. The system can cost less than conventional methods.

Technologies for automated mapping and extraction of transitions in mapping landscape

At the core of stakes, we have combination of artificial intelligence (AI) and proprietary Mobile Mapping System that could help hasten autonomous driving. We also havehighly precise three-dimensional maps that provide static information of roads and surrounding objects, intending to form the basis for dynamic maps indispensable for autonomous driving.
With its new technologies for automated mapping and extraction of transitions in mapping landscape based on artificial intelligence (AI) and the company’s own Mobile Mapping System (MMS) ,Mitsubishi Electric aims to contribute to the early implementation of maps that offer constantly updated dynamic information, such as traffic signals and information about surrounding vehicles etc., for safe, highly precise autonomous driving.

Lenovo is integrating a 3D Time-of-Flight (ToF) camera

Camera modules in smartphones evolve rapidly, so that all major players have adopted dual cameras. With the Phab2Pro, Lenovo chooses an exciting approach as augmented reality steadily plays a bigger part in consumer life, by integrating a 3D Time-of-Flight (ToF) camera. The module features three cameras: one with high resolution, a global shutter motion detector and a Near Infra-Red (NIR) sensor.

3D Time-of-Flight (ToF) sensors for consumer applications

Very exciting to recall that, the Lenovo Phab2Pro (smartphone) brings totally new functionality based on the Google Tango Project. This project, a collaboration including Infineon, pmd and Sunny Optical, has developed 3D ToF sensors for consumer applications.
For those who are unfamiliar, the Phab2Pro implements this technology using a tri-camera sensor. The subsystem features a 16 megapixel resolution CMOS image sensor (CIS) from Samsung, a VGA resolution CIS with global shutter technology from Omnivision, and a 38 kilopixel resolution 3D Image Sensor from the collaboration between Infineon and pmd integrated into a subsystem with a NIR vertical-cavity surface-emitting laser (VCSEL). I can also observe that, to provide the 3D scene, the tri-camera's high-resolution camera supplies the texture and the global shutter camera supplies the motion-tracking. Finally, the ToF sensor supplies the depth perception at a high rate thanks to the VCSEL emitter, which gives the phone the abilit…

Market Dynamics of the global image recognition market

Many analysts agree on the current realities as follow: Drivers Increasing Use of Image Recognition Applications Increasing Demand for Security Applications and Products Enabled With Image Recognition Functions Technology Acceptance By Various Companies in Different Verticals Increasing Use of High Bandwidth Data Services Restraints High Cost of Installation of Image Recognition Systems Opportunities Increasing Demand for Big Data Analytics Increasing Demand of Brand Recognition Among End-User Challenges Low Resolution Image Size and Storage

The growth of the image recognition market explained

I can recall that, the growth of the image recognition market can be attributed to the rising use of high bandwidth data services in retail and BFSI sector. Smartphones and devices with cameras are attracting vendors to invest in the market. Increasing demand for security applications and products enabled with image recognition functions is also influencing the growth of this market.
Various companies in different sectors, such as retail, automotive, healthcare, and defense, are significantly adopting image recognition technology. Low-resolution image size and storage act as a challenge for the growth of the market. Owing to the technological advancements in image recognition, key vendors are focusing on launching next generation solutions and services. Research and Markets reveals that, the image recognition market is estimated to grow from USD 15.95 Billion in 2016 to USD 38.92 Billion by 2021, at the CAGR of 19.5% during the forecast period.

Mobile robots are also already penetrating dairy farms

Proudly, one can observe that, Robotic and drones have already started to quietly transform many aspects of agriculture. For instance, thousands of robotic milking parlours have been installed worldwide, creating nearly a $1.9bn industry that is projected to grow to $8bn by 2023. When it comes to Mobile robots, already they are penetrating dairy farms, helping automate tasks such as feed pushing or manure cleaning.

Core function drones provide to Agriculture

It is now obvious that, the progress of drones is by no means limited to spraying. Their core function is to provide detailed aerial maps of farms, enabling farmers to take data-driven site-specific action. Light-weight low-cost drones are often loaded with small multi-spectral sensors, measuring key indicators about plant health, yields, water stress levels, nitrogen deficiency , to name a few. Agriculture will be a major market for drones, reaching over $480m in 2027. Unmanned remote-controlled helicopters have already been spraying rice fields in Japan since early 1990s. Indeed, this is a maturing technology/sector with overall sales in Japan having plateaued. This market will benefit from a new injection of life as suppliers diversify into new territories and as low-cost light-weight sprayer drones enter the market.

Cloud Computing Market in Europe

While European enterprises continue to see IT security as a major barrier to adoption, it is clear that, Organizations are tapping into cloud solutions to reduce expenditure, widen productivity and scale, and increase computing power in light of Big Data issues. The European Cloud Computing industry is expected to generate total revenues of $30bn in 2017.