MOBOTIX launches new camera platform - M15
MOBOTIX launches new camera platform - M15

MOBOTIX AG recently launched the new camera platform, M15. A platform which is based on the new MOBOTIX 5 Megapixel Technology, it offers two exchangeable sensor modules and further builds on MOBOTIX‘ innovative camera platform concept. "The M15 offers the latest in MOBOTIX‘ camera system technology and follows a proud tradition that we  have started over 13 years ago with the M1 and have continued with the M10 and M12," says Dr. Ralf Hinkel, founder of MOBOTIX AG. "We are confident that the M15 will be breaking ground in many ways; technically, as a product platform concept, design-wise and because it is developed in a unique combination between end-users and MOBOTIX". The M15 is naturally developed around the MOBOTIX decentralised system technology which saves costs, management and network resources for the end-user. The M15 product platform offers two exchangeable 5 Megapixel sensor modules which are exactly the same modules as for the recently launched S15. "We have developed the M15 in close cooperation with our end-users and partners. Our end-users want a dynamic platform that can change with their current and future needs, and our partners want a platform for many different applications,“ continued Dr. Hinkel. As the sensor modules can be easily exchanged by the end-user, they will always have an up-to-date camera surveillance system regardless of original mounting place and, at that time, the intended focus of that specific camera. “The end-users and our partners can today choose up to 5 completely different sensor combinations for this platform and in the future there will be even more," said Dr. Hinkel. By using 5 Megapixel sensors for the M15 camera platform, the users will gain more than four times better light sensitivity in all conditions. The new sensor technology offers a frame rate of up to 30 frames per second and the zoom capabilities are increased by 27% in colour and by more than 200% in black-and-white. "It is important to emphasize that the M15 is a Day-and-Night camera not a day/night. The difference is huge between these two concepts, the M15 sensor modules, depending on configuration, are always able to offer one day and one night image simultaneously, which is especially important in low light conditions as well as in no light," commented Dr. Hinkel. The new M15 camera platform is IP66 certified and is successfully tested at a temperature range from -30 °C to +60 °C. Following MOBOTIX established product strategy, the M15 does not need any additional housing, fans, heating etc. “The user can take our new camera platform and literally install it wherever he or she wants to. We have people using our products in very extreme environments and they will be very happy with the M15,” said Dr. Hinkel. The M15 camera platform only needs around 5 watt to be fully functional, which both saves costs and energy for the users. “The new M15 is marked with the MOBOTIX Green IP-Video logo for being exceptionally environment-friendly, which is a social conscience initiative that MOBOTIX have taken and I feel very strongly about,” concluded Dr. Ralf Hinkel. A special advantage: The M15 is fully integrated with the new revolutionary MxActivitySensor technology for intelligent motion detection that reduces false alarms and errors considerably. The M15 is available over authorised MOBOTIX distributors and partners.

Add to Compare
MOBOTIX’s new thermal radiometry camera series helps to prevent fires
MOBOTIX’s new thermal radiometry camera series helps to prevent fires

 MOBOTIX has launched a new series of thermal camera products, equipped with a new type of thermal sensing technology to realise automatic events, based on absolute temperatures within -40°C to +550°C (or -40°F to +1022°F). This new technology is perfect to generate automatic alarms, defined by temperature limits or temperature ranges, which is vital to detect potential fire or heat sources. At the same time, MOBOTIX provides a free software update to upgrade existing thermal cameras with thermal spot metering in the image centre. Within the available temperature range of -40°C to +550°C (or -40°F to +1022°F) and a thermal sensitivity of 0.05°C (NETD=50mK), different temperature conditions can be easily defined within the new TR (Thermal Radiometry) window or over the whole sensor image with a typical accuracy of ±10°C. Up to 20 multiple temperature events can be defined at the same time. Spot metering, which measures temperature related to 4 pixels at the image centre, is also improved in the new thermal TR products with a typical accuracy of ±10°C. These new releases will help to prevent bigger damages in industrial and commercial premises, at manufacturing and logistic sites, recycling facilities, forests, etc. MOBOTIX Thermal Radiometry (TR) is available in its popular M15, and as a sensor module in the S15 dual camera system. Furthermore, TR is also available as S15 PT-mount sensor head. Both S15 thermal modules can be set up as dual thermal system for most flexible usage or as the perfect combination of thermal and optical sensor technology to ensure the most reliable detection results and visual verification at the same time.

Add to Compare
MOBOTIX launches S14 FlexMount  - The world’s first flexible double hemispheric camera
MOBOTIX launches S14 FlexMount - The world’s first flexible double hemispheric camera

The S14 FlexMount from MOBOTIX, the world’s first flexible double hemispheric camera, is now available. The camera, which is available in both mono (S14M) and dual (S14D) versions, features miniature lens units and offers a wide range of application opportunities. For instance, the S14D can be equipped with two hemispheric lens units with integrated microphone that are connected to the main housing via cables. This makes it possible to fully secure two rooms located next to or on top of one another with just one single S14. The slim design of the module units, which are available in white and black, permit an extremely discreet installation. Two rooms secured with one single camera The S14 FlexMount offers the option to set up two hemispheric lens units simultaneously in order to completely cover two adjacent rooms with just one single S14D. When installed in a certain way, the S14D can also see around corners or secure indoor and outdoor areas at the same time. The two sensors allow the S14 to generate two distortion-corrected, high-resolution 180° panorama images, each with a resolution of 3.1 megapixels. All other MOBOTIX lenses, from super-wide angle to tele lens, will be available in the near future as day or night versions.The S14 is the world's first hemispheric day-and-night camera. When both modules with black-and-white and colour sensors are mounted directly next to each other and cover the same area, the camera automatically chooses the best available mode depending on the lighting conditions. This provides for excellent colours in daylight as well as superb light sensitivity in dark environments. Panning and zooming into the image is done purely electronically. The user is provided with detailed views and other image sections without any mechanical movement, meaning that there is no wear-and-tear to the camera and no maintenance is required. Weatherproof, discreet and energy efficient Both module units and the separate housing with the latest dual camera board are weatherproof in accordance with IP65 and operate in a temperature range of -30°C to +60°C (-22°F to +140°F). The flat housing, including flash memory with up to 64 GB and all external connectors (Ethernet, MiniUSB, MxBus), can be installed discreetly and with optimal protection behind a wall or ceiling panel so that only the lens units in their ultra-compact protective housing are visible. Power is supplied very cost effective via a network cable (PoE). At less than five watt-hours, the energy consumption is extremely low. Wide range of application opportunities The camera's technical features and very discreet mounting open up a whole range of application opportunities. In L-shaped rooms, for example, the two sensor modules can be positioned at the corner in correct angles to each other, therefore capturing the entire room without any blind spots. Therefore, the S14 is particularly well-suited for use in hotels, banks and retail stores where the highest levels of security and discretion are required. The S14 can also demonstrate its strengths at security gates and in offices. MOBOTIX also offers the appropriate installation accessories for mounting the sensor module on thicker walls. Using several extension pieces (each approx. 40 mm), longer "tunnel holes" through a wall can also be bridged. MOBOTIX software included free of charge As usual with all MOBOTIX products, the complete software for configuration and operation of the camera is integrated directly into the camera. Additionally, professional video management software can be downloaded from the website free of charge.

Add to Compare
MOBOTIX p25 6MP indoor ceiling camera with 6MP moonlight sensor technology
MOBOTIX p25 6MP indoor ceiling camera with 6MP moonlight sensor technology

The new benchmark in lowlight for objects in motion The brand-new MOBOTIX 6MP cameras have an outstanding increase of light sensitivity of more than 100-times than the former 3MP cameras. The monochrome version reaches even a 300-times higher sensitivity than the previous series. Instead of one full second of exposure time the new 6MP systems can select only 1/100 s which results in capturing even fast moving objects in low light conditions. Short exposure times are essential In security monitoring every moment and therefore every single frame of a video recording has to be as sharp as possible. For moving objects this implies the necessity of short instead of long exposure times. Unfortunately a short exposure time of 1/100 s grabs 10-times less light than a 1/10 s. Especially in low light conditions, the lens, the image sensor itself and the image processing for sure have to be very sophisticated­ to generate a sharp and crisp image of the moving object. Only a sharp image is a proof In dark scenes long exposure times of up to 1 second create bright images and visible static objects. Perfect to acknowledge objects in darkness. But if objects are moving,­ long exposure times will create blurring or ghost images, and make verification of moving objects nearly impossible. In security applications­ moving objects are of utmost importance,­ therefore short exposure times are essential to understand what‘s going on. Some manufacturers are using a combination of technologies like adding frames to generate a brighter image (e. g. Lightfinder, HDR, etc.). However, with this adding and overlaying of subsequent frames, small details or objects in the scene could be suppressed­ or distorted, which is inacceptable in security­ applications. Optimised for best performance This huge increase in light sensitivity was achieved by several means: wider sensor with bigger pixels to catch more light, a hardware noise reduction filter directly at the sensor, a new sophisticated lens with a better light transmission, and an improved image processing software reducing the noise of low light images. This is called the new MOBOTIX Moonlight Technology.

Add to Compare

IP cameras - Expert commentary

The benefits and challenges of in-camera audio analytics for surveillance solutions
The benefits and challenges of in-camera audio analytics for surveillance solutions

Audio is often overlooked in the security and video surveillance industry. There are some intercom installations where audio plays a key role, but it’s not typically thought about when it comes to security and event management. Audio takes a back seat in many security systems because audio captured from a surveillance camera can have a different impact on the privacy of those being monitored. Audio surveillance is therefore subject to strict laws that vary from state to state. Many states require a clearly posted sign indicating audio recording is taking place in an area before a person enters. Analytic information derived from audio can be a useful tool and when implemented correctly, removes any concerns over privacy or legal compliance. Audio analytics on the edge overcomes legal challenges as it never passes audio outside of the camera Focused responses to events Audio analytics processed in the camera, has been a niche and specialised area for many installers and end users. This could be due to state laws governing audio recording, however, audio analytics on the edge overcomes legal challenges as it never passes audio outside of the camera Processing audio analytics in-camera provides excellent privacy since audio data is analysed internally with a set of algorithms that only compare and assess the audio content. Processing audio analytics on the edge also reduces latency compared with any system that needs to send the raw audio to an on-premises or cloud server for analysis. Audio analytics can quickly pinpoint zones that security staff should focus on, which can dramatically shorten response times to incidents. Audio-derived data also provides a secondary layer of verification that an event is taking place which can help prioritise responses from police and emergency personnel. Having a SoC allows a manufacturer to reserve space for specialised features, and for audio analytics, a database of reference sounds is needed for comparison Microphones and algorithms Many IP-based cameras have small microphones embedded in the housing while some have a jack for connecting external microphones to the camera. Microphones on indoor cameras work well since the housing allows for a small hole to permit sound waves to reach the microphone. Outdoor cameras that are IP66 certified against water and dust ingress will typically have less sensitivity since the microphone is not exposed. In cases like these, an outdoor microphone, strategically placed, can significantly improve outdoor analytic accuracy. There are several companies that make excellent directional microphones for outdoor use, some of which can also combat wind noise. Any high-quality external microphone should easily outperform a camera’s internal microphone in terms of analytic accuracy, so it is worth considering in areas where audio information gathering is deemed most important. In-built audio-video analytics Surveillance cameras with a dedicated SoC (System on Chip) have become available in recent years with in-built video and audio analytics that can detect and classify audio events and send alerts to staff and emergency for sounds such as gunshots, screams, glass breaks and explosions. Having a SoC allows a manufacturer to reserve space for specialised features. For audio analytics, a database of reference sounds is needed for comparison. The camera extracts the characteristics of the audio source collected using the camera's internal or externally connected microphone and calculates its likelihood based on the pre-defined database. If a match is found for a known sound, e.g., gunshot, explosion, glass break, or scream, an event is triggered, and the message is passed to the VMS. If a match is found for a known sound, e.g., gunshot, explosion, glass break, or scream, an event is triggered, and the message is passed to the VMS Configuring a camera for audio analytics Audio detectionThe first job of a well-configured camera or camera/mic pair is to detect sounds of interest while rejecting ancillary sounds and noise below a preset threshold. Each camera must be custom configured for its particular environment to detect audio levels which exceed a user-defined level. Since audio levels are typically greater in abnormal situations, any audio levels exceeding the baseline set levels are detected as being a potential security event. Operators can be notified of any abnormal situations via event signals allowing the operator to take suitable measures. Finding a baseline of background noise and setting an appropriate threshold level is the first step. Installers should be able to enable or disable the noise reduction function and view the results to validate the optimum configuration during setup Noise reductionA simple threshold level may not be adequate enough to reduce false alarms depending on the environment where a camera or microphone is installed. Noise reduction is a feature on cameras that can reduce background noise greater than 55dB-65dB for increased detection accuracy. Installers should be able to enable or disable the noise reduction function and view the results to validate the optimum configuration during setup. With noise reduction enabled, the system analyses the attenuated audio source. As such, the audio source classification performance may be hindered or generate errors, so it is important to use noise reduction technology sparingly. Audio source classificationIt’s important to supply the analytic algorithm with a good audio level and a high signal-to-noise ratio to reduce the chance of generating false alarms under normal circumstances. Installers should experiment with ideal placement for both video as well as audio. While a ceiling corner might seem an ideal location for a camera, it might also cause background audio noise to be artificially amplified. Many cameras provide a graph which visualises audio source levels to allow for the intuitive checking of noise cancellation and detection levels. Analytics take privacy concerns out of the equation and allow installers and end users to use camera audio responsibly Messages and eventsIt’s important to choose a VMS that has correctly integrated the camera’s API (application programming interface) in order to receive comprehensive audio analytic events that include the classification ID (explosion, glass break, gunshot, scream). A standard VMS that only supports generic alarms, may not be able to resolve all of the information. More advanced VMS solutions can identify different messages from the camera. Well configured audio analytics can deliver critical information about a security event, accelerating response times and providing timely details beyond video-only surveillance. Analytics take privacy concerns out of the equation and allow installers and end users to use camera audio responsibly. Hanwha Techwin's audio source classification technology, available in its X Series cameras, features three customisable settings for category, noise cancellation and detection level for optimum performance in a variety of installation environments.

Artificial Intelligence (AI) in physical security systems: Trends and opportunities
Artificial Intelligence (AI) in physical security systems: Trends and opportunities

If you’ve been paying attention over the last twelve months, you will have noticed that deep learning techniques and artificial intelligence (AI) are making waves in the physical security market, with manufacturers eagerly adopting these buzzwords at the industry's biggest trade shows. With all the hype, security professionals are curious to know what these terms really mean, and how these technologies can boost real-world security system performance. The growing number of applications of deep learning technology and AI in physical security is a clear indication that these are more than a passing fad. This review of some of our most comprehensive articles on these topics shows that AI is an all-pervasive trend that the physical security industry will do well to embrace quickly. Here, we examine the opportunities that artificial intelligence presents for smart security applications, and look back at how some of the leading security companies are adapting to respond to rapidly-changing expectations: What is deep learning technology? Machine Learning involves collecting large amounts of data related to a problem, training a model using this data and employing this model to process new data. Recently, there have been huge advances in a branch of Machine Learning called Deep Learning. This describes a family of algorithms based on neural networks. These algorithms are able to learn efficiently from example, and subsequently apply this learning to new data. Here, Zvika Ashani explains how deep learning technology can boost video surveillance systems. Relationship between deep learning and artificial intelligence With deep learning, you can show a computer many different images and it will "learn" to distinguish the differences. This is the "training" phase. After the neural network learns about the data, it can then use "inference" to interpret new data based on what it has learned. For example, if it has seen enough cats before, the system will know when a new image is a cat. In effect, the system “learns” by looking at lots of data to achieve artificial intelligence (AI). Larry Anderson explores how new computer hardware - the Graphic Processing Unit (GPU) – is making artificial intelligence accessible to the security industry. Improving surveillance efficiency and accuracy with AI Larry Anderson explains how the latest technologies from Neurala and Motorola will enable the addition of AI to existing products, changing an existing solution from a passive sensor to a device that is “active in its thinking.” The technology is already being added to existing Motorola body-worn-cameras to enable police officers to more efficiently search for objects or persons of interest. In surveillance applications, AI could eliminate the need for humans to do repetitive or boring work, such as look at hours of video footage. Intelligent security systems overcome smart city surveillance challenges AI technology is expected to answer the pressing industry questions of how to use Big Data effectively and make a return on the investment in expensive storage, while maintaining (or even lowering) human capital costs. However, until recently, these expectations have been limited by factors such as a limited ability to learn, and high ongoing costs. Zvika Ashani examines how these challenges are being met and overcome, making artificial intelligence the standard in Smart City surveillance deployments. Combining AI and robotics to enhance security operations With the abilities afforded by AI, robots can navigate any designated area autonomously to keep an eye out for suspicious behaviour or alert first responders to those who may need aid. This also means that fewer law enforcement and/or security personnel will have be pulled from surrounding areas. While drones still require a human operator to chart their flight paths, the evolution of artificial intelligence (AI) is increasing the capabilities of these machines to work autonomously, says Steve Reinharz. Future of artificial intelligence in the security industry Contributors to SourceSecurity.com have been eager to embrace artificial intelligence and its ability to make video analytics more accurate and effective. Manufacturers predicted that deep learning technology could provide unprecedented insight into human behaviour, allowing video systems to more accurately monitor and predict crime. They also noted how cloud-based systems hold an advantage for deep learning video analytics. All in all, manufacturers are hoping that AI will provide scalable solutions across a range of vertical markets. 

Video surveillance technologies evolve to meet data and cybersecurity challenges
Video surveillance technologies evolve to meet data and cybersecurity challenges

The Internet of Things (IoT) is having a significant and ever-changing impact on the way we view video security. Today, cameras are expected to be so much more than devices with which to simply capture images; they need to be far smarter than that. These future-facing cameras are becoming an integral part of the vast digital connectivity infrastructure, delivering a parallel performance as intelligent sensors with the ability to extract the kind of invaluable data that helps businesses make improvements in the area of video security, and beyond. However, as the list of possibilities grows, so too does the risk of unauthorised access by cybercriminals. We should all be aware that a single weak link in a communications infrastructure can give hackers access to sensitive data. That’s the bad news. Safeguarding data and utilising deep learning The good news is cybercrime can be avoided by employing a data security system that’s completely effective from end-to-end. One technological advancement that the trend-spotters are predicting will become part of the video security vocabulary is ‘deep learning’ Once this level of safeguarding is in place you can begin to confidently explore the technologies and trends happening now, and those on the horizon. So, what will be having an influence on surveillance in 2018? Well, according to IHS Markit, one technological advancement that the trend-spotters are predicting will become part of the video security vocabulary is ‘deep learning’, which uses algorithms to produce multiple layers of information from the same piece of data, therefore emulating the way the human brain absorbs innumerable details every second. In Europe, GDPR compliance will also be a big talking point as new principles for video surveillance data collection, use limitation, security safeguards, individual participation and accountability are introduced. And, as the popularity – and misuse – of drones continues to rise, the recent developments in drone detection technology will be particularly welcomed by those whose primary concern relates to large areas, such as airport perimeter security. The future of 'smart' video analytics An important feature of today’s intelligent cameras is the ability to provide smart video analytics. The Bosch ‘i’ series, for example, offers a choice of formats – Essential Video Analytics and Intelligent Video Analytics. Essential Video Analytics is geared toward regular applications such as small and medium businesses looking to support business intelligence (e.g. inter-network data transfer), large retail stores and commercial buildings for advanced intrusion detection, enforcing health and safety regulations (no-parking zones or detecting blocked emergency exits) and analysing consumer behaviour. The camera-based, real-time processing can also be used to detect discarded objects, issue loitering alarms and detect people or objects entering a pre-defined field. Intelligent Video Analytics provides additional capabilities. It is designed for demanding environments and mission-critical applications, such as the perimeter protection of airports, critical infrastructures and government buildings, border patrol, ship-tracking and traffic-monitoring (e.g. wrong-way detection, traffic-counts and monitoring roadsides for parked cars: all vital video security solutions). An important feature of today’s intelligent cameras is the ability to provide smart video analytics Intelligent Video Analytics can also differentiate between genuine security events and known false triggers, such as challenging environments created by snow, wind (moving trees), rain, hail, and water reflections. For more expansive areas, like an airport perimeter fence, the system has the range and capability to provide analysis over large distances. And, if a moving camera is employed, it is also possible to capture data on objects in transit when used in conjunction with the Intelligent Tracking feature. For roadside use, Intelligent Video Analytics systems, such as the Bosch MIC IP range, are resistant to vibrations and can still operate in extreme weather conditions, continuing to detect objects in heavy rain or snow.  Evolving cameras past surveillance It’s becoming ever clearer that the IoT is transforming the security camera from a device that simply captures images, into an intelligent sensor that plays an integral role in gathering the kind of vital business data that can be used to improve commercial operations in areas beyond security. For example, cities are transitioning into smart cities. The capabilities of an intelligent camera extend to the interaction and sharing of information with other devices (only those you have appointed) With intelligent video security cameras at the core of an urban infrastructure smart data can be collected to optimise energy consumption via smart city lighting that responds to crowd detection and movement. Cameras can also be used to improve public transport by monitoring punctuality and traffic flow based on queue lengths, with the ability to control traffic lights an option should a situation require it. As the urban sprawl continues and this infrastructure grows, the need for more knowledge of its use becomes more essential, necessitating the monitoring technology developed for use by human operators to evolve into smart sensing technology, that no longer just provides video feeds, but also uses intelligent analytics and sophisticated support systems. These systems filter out irrelevant sensor data and present only meaningful events, complete with all relevant contextual data to operators to aid their decision-making. Expanding the video security camera network Today, video analytics technology has tangible benefits for human operator surveillance, and delivers KPIs that are highly relevant to transport operators, planners and city authorities. As an existing infrastructure, a video security camera network can be improved and expanded by installing additional applications rather than replaced. From a business perspective, that means greater value from a limited investment. Thereafter, the capabilities of an intelligent camera extend to the interaction and sharing of information with other devices (only those you have appointed), image and data interpretation, and the ability to perform a variety of tasks independently to optimise both your safety and business requirements. The fact is, cameras see more than sensors. Sounds obvious, but a conventional sensor will only trigger an alarm when movement is detected, whereas a camera can also provide the associated image and information like object direction, size, colour, speed or type, and use time stamps to provide historical information regarding a specific location or event. Based on this evidence, the video security camera of today is more than ready for the challenges of tomorrow.