Video-on-demand meets video surveillance in a new product released by Keystone Electronic Solutions, a South African electronics research and development company.
Project V, a aimed at providing centrally managed video surveillance, works through either event or alarm triggered video streaming, or via a video-on-demand interface.
The stream-on-trigger video platform is not only able to provide Digital Video Recording (DVR) archiving on a central server, but also at remote sites. Integration with customer systems, such as network management systems, access management systems, trouble ticket management and reporting tools, can be provided through an Application Program Interface (API).
Project V consists of remote site equipment and a central surveillance platform. All user access to the platform is provided through a website.
“As far as we are aware, there are no other products available today that can match this technology,” says John Eigelaar, Director and co-founder of Keystone Electronic Solutions. “We have had a dedicated team work on this project over the past few months and have had a few field trials with select customers. Project V can overcome a number of challenges for our customers – it makes security and surveillance much easier and more effective, and thus creates a huge cost saving.”
Keystone provided the following overview of main features:
- Record keeping:
Certain video triggers can be set up to either start or stop the video recording and streaming.
Real-time streaming makes it possible for security teams to determine how to respond to a security incident. For example, in the event of intruder detection alarm, security teams will be alerted and will be able to see live video streaming. They can then more effectively judge how to respond to the particular event.
The bandwidth can be selected on each on-site unit. Depending on the selected bandwidth, the AV video will either be streamed to the Project V server or recorded locally on the board. In both cases the alarm events will be transmitted across the CnE over the network. Operators can also request AV streams/recording from the web graphical user interface (GUI).
- Audio visual:
The RSM unit is permanently connected to the available IP cameras and will pull available AV streams from the cameras depending on the alarm/event triggered. Streams can be stored locally or be pushed up to the Project V server, for remote recording or viewing of the stream.
- NMS Backhaul:
The video surveillance platform allows for the backhaul of the CnE pipe and the AV streams, either across an Ethernet WAN interface or the onboard 3G GSM modem.
- Camera integration:
The platform integrates with any IP camera. Additionally, any I/O interface that a camera might provide (such as zone or movement triggers) can be integrated with the platform as part of the site security profile.
The platform has been designed to be highly scalable from an interface point of view. The number of I/Os available to the system is easily scaled from a standalone device to a large installation by adding further RSM IO modules.
Motor Racing meets Machine Learning
The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK
The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.
Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.
Now there’s a new name to add to the roster of technology giants driving the future.
Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com, last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.
AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.
But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.
AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.
Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.
As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.
“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.
“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”
Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information.
During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.
This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.
“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.
LG rethinks portable speakers
LG adds three sizes to its XBoom Go portable speaker line in a portable revision, writes BRYAN TURNER.
Portable Bluetooth speakers are fairly commonplace at a pool party because they’re battery-powered. The only issue is that louder speakers usually distort the music or break the bank. The LG XBoom aims to change this.
LG has partnered with Meridian Audio to produce great sounding speakers that can go loud without distorting the audio. Meridian Audio is an expert in high-performance, high-fidelity audio experiences. The company is best known for producing the industry’s first audiophile-quality compact disc player and provide audio equipment to McLaren and Jaguar Land Rover.
The Bluetooth software in the XBoom Go is Qualcomm aptX HD compatible, meaning that 24bit vinyl-quality audio can be played through this speaker over Bluetooth instead of standard-fidelity audio.
The major phone assistants feature on these speakers, with tethered Google Assistant or Apple Siri functionality from one’s smartphone. This makes it very convenient to use the voice assistant button to skip tracks and change music when one’s hands are wet.
Three models of the XBoom Go series – the PK3, PK5 and PK7 – offer different audio functions depending on the audio needs of the user. Best fits for these speakers are:
PK3 – The Pool Friendly Speaker: The PK3 is IPX7 water resistant, up to 1 metre for 30 minutes, making this speaker accident proof at pool parties. Boasting up to 12 hours of playback from its built-in battery, this speaker will last as long as the party.
PK5 – The Party Friendly Speaker: Even if the lunch braai turns into a midnight feast, this speaker will play throughout as its battery lasts up to 18 hours. Clear Vocal technology is added to the PK5, which reduces audio imperfections from the music for a sharper sound. It is also water and splash resistant and has a handle, allowing for it to be easily carried. Built-in LED lights which pulse with the beat of the music on this speaker provide a light show for any song.
PK7 – The Audiophile’s Speaker: With a battery life that lasts for up to 22 hours, the PK7 also contains an LED light to the rhythm of the sound. The speaker integrates a convenient handle grip that allows for it to be transported securely. The powerful PK7 Bluetooth speaker also distributes its high frequencies across two separate tweeters for more precise sonic detail.
Overall, LG’s XBoom PK portable speakers are a phenomenal set of high-quality wireless speakers.