Just as drones popularity has been increasing rapidly in the past few years they are perceived as the instruments allowing to go beyond the bounds and thus being adopted massively by the entertainment industry. Here are the facts behind the dazzle which will make you consider a drone light show for your next event!
Today, businesses need a data center to be compact-size, effective, and cost-efficient, but, above all, perfectly safe to host the most valuable data. Here are five main ways to ensure secure and uninterrupted data center operations.
Free сooling
How to reduce OPEX and improve the performance of a data center? Optimize on-site cooling, which is the second most expensive item on the electricity bill after IT load.
Solution: Take region’s temperature statistics for the last 50 years, calculate annual energy consumption for equipment from various vendors, and finally… Start using outdoor air to the fullest. This technology is called free cooling.
How it works: There are two main types of free cooling: direct and indirect. When it comes to the direct method, outdoor air, once filtered, goes directly to computer rooms, with key benefits here being low energy consumption and implementation cost, as well as simple design. Even though indirect free cooling is less effective as it requires heat exchangers to convey the air through, this method ensures that the same clean air circulates in computer rooms.
Li-ion batteries
A question of the day: what can replace lead acid batteries, the most common uninterrupted power supply (UPS) units for data centers? It seems like li-ion batteries, which brought their developers the 2019 Nobel Prize in Chemistry, are the best way to go. Being much lighter than traditional ones, they can even be mounted on ceiling and walls that can hardly sustain the weight of lead. This is very important as many data centers are created in already existing buildings. Moreover, li-ion batteries are considerably smaller and thus don’t occupy much space in a server room.
How it works: UPS units ensure that a data center keeps working in the event of a power shutdown until either the primary power source restoration or switchover to a backup source. In addition to being light and compact, a li-ion battery features high power capacity, long service life (about 10 years) and fast charging.
Liquid cooling
Just a few years ago, this cooling method was only used for supercomputers, while today it is also increasingly the case for regular data centers. Such systems are small and consume minimum energy (power is only needed for several low-flow pumps).
How it works: Server equipment is fully submerged in a leak-proof slightly open tank containing liquid dielectric coolant, which is evenly distributed to keep constant temperature.
Fire-fighting systems
How to put out a fire in a data center? Today’s fire-fighting systems for data centers can be divided into two types: water mist and nitrogen.
Water-mist systems create microscopic droplets (100-150 microns) of distilled water that are considered safe for data center equipment. These systems have minimum water consumption and can be effectively used in both sealed and unsealed rooms, even with people still being nearby.
Nitrogen fire-extinguishing systems displace oxygen by nitrogen generated directly in the protected space, thus completely suppressing fire. This method is also safe for people.
How it works: Modern aspirating fire detection systems can raise alert even before visible smoke particles fill the room. Unlike passive smoke detectors, this system actively draws air samples through holes within pipes that run throughout the protected area to ensure continuous analysis. Thanks to such systems, data centers rarely catch actual fire.
Physical security
Several innovative technologies are widely leveraged at data centers against intruders.
How it works: The above-listed systems ensure multi-tiered security, with each next tier making it more difficult to break into a computer room.
Innovations are spreading tentacles in airports around the globe to surround travelers with comforts and take the excessive strain out of transport hubs. So let’s take a look at the most popular everyday objects you might not even guess are smart.
Combining versatile technologies, the global smart airport market is estimated to reach USD 31.10 billion by 2026 growing at a CAGR of 11.2% during the forecast period, according to a new Market Study Report.
Self-service kiosks
The growing implementation of self-service kiosks at airports is driven by travelers’ desire to save check-in time, enjoy personalized services, and obtain updates in real time.
Biometrics
The face recognition and biometrics identification technologies are actively adopted in the international airports. Once a traveler has submitted a passport and registered in the system, his or her face turns into a single travel token, like a traditional passport. For instance, Hong Kong International Airport (HKIA) embedded powerful intelligent technologies to scan and match traveler biometrics — an eye retina and fingerprint — with their passport chip data.
Dubai International Airport was among the first airports to offer smart security gates with automatic identification. Anyone with a machine-readable passport can simply use the smart gate and pass further.
Ads in crowded areas
Another airport leveraged Wi-Fi hotspots to detect passengers’ whereabouts and the exact time spent there. Following the aggregated data analysis, the airport placed ads in the most crowded locations, thus increasing its advertising earnings.
Robotics-enabled luggage storage
Domodedovo International airport, one of the largest airports in Eastern Europe with annual passengers’ flow of +30M, offers luggage check-in and drop-off 24 hours before the scheduled flight. Early birds’ bags go to an automated short-term luggage storage, where six steel arm robots move the chipped bag boxes running along rails to navigate through 12 three-meter shelves at a speed of 14 km/h. When the time comes, the robots are automatically triggered to bring certain bags to a certain flight in just two minutes.
Beacon-based navigation
Beacon-based indoor navigation systems are becoming increasingly popular, as well as multiple wireless sensors helping control air quality and lighting and observe presence of people in the area. In addition, these sensors can contribute to not only automation and engineering system management tasks, but also building of heat maps of popular passenger places across airport to adjust space lease pricing policy.
Beacons also provide the fastest and free to access Wi-Fi in Dubai International Airport. The “world’s fastest airport Wi-Fi” required the installation of new wireless access points throughout the airport, and each of these also includes a Bluetooth Low Energy (BLE) beacon.
Drone detection
In July 2019, Muscat airport first in the World got drone detection system: it detects drones and other devices using radio frequency to protect the surrounding areas of the airport.
“If you look at IoT apps, most are either security or manufacturing related. We see the lack of demand from the airports still following their passenger management routine. However, in the coming years, we will see how IoT enters consumer-related markets with digital helpers, robots, cashier-less shops and many more personalized services provided even before you arrive to the place. Travel experience will become personalized as well,” said Alexander Belyaev, NNTC Technical Director.
Robotic Process Automation (RPA) is about optimizing individual processes and freeing up people for human-only tasks. Robots will never completely replace humans, that’s for sure, since feelings, emotions, and critical thinking are all beyond machines’ capability. However, robots excel at calculations and simple tasks – no hard choices or emotional investing.
According to PwC Middle East research, the AI market in the Middle East will rise to $320 billion by 2030. There is a strong focus on RPA of customer care services: in 2017, the Dubai Electricity and Water Authority (DEWA) announced recruitment of five robots to its Customer Happiness Centres. Retailers also tend to engage robots. Pepper, a world famous robot, welcomes visitors at several UAE banks and salespoints, defines customer’s gender and provides recommendations for a retail demo or special offers in the store.
For robots, the retail sector is an ideal testing field and promising application area. Just look at numerous use cases, like automated store shelve control (merchandising, stock and price tag checks) using robotic carts with optical recognition module – a godsend for merchandisers, or cashier workload calculation based on video analytics to better schedule salesforce working time in a shopping space. And what about PoS self-service payment system powered by face recognition? Such a fare system was rolled out in Chinese subway and Amazon Go self-service stores so we can say for sure that it really works.
In warehouses, robots handle and sort products. Besides other things, Amazon is famous for its robotized warehouses, promptly processing millions of orders every day. Dozens of robotized auto-loaders, as little as a common vacuum cleaner, easily move heavy shelve stands with goods to operators who just take necessary items from the shelves. As a result, with a help of a robot, one operator does the job of 6-7 persons, with order batching becoming cheaper as well. With the routes determined in advance, robots avoid collisions and easily transport big shelve stands within a limited territory. Adler, a German clothing chain, leverages robots for warehouse inventory control. Every night, robots called Tory scan RFID tags on goods and generate stock reports.
However, robots cannot replace all sales personnel when it comes to a bit more sophisticated tasks, as we can see from Amazon’s experiment with robotized stores. The company tested its first Amazon Go stores back in 2016, with 10 such stores currently operating in the U.S. No cash desks, cashiers, consultants or queues there. At the entrance, shoppers scan their Amazon Accounts and at once find themselves among smart sensors. The system tracks what goods shoppers take from shelves and how they move across the store, and automatically debits the necessary sum from the buyer’s account once they exit the supermarket. Despite the marvelous idea and company’s attempts to improve the system, the stores regularly face difficulties as tracking more than 20 people moving across the store turned out to be a real challenge for the cameras. If a shopper takes an item, reads a tag and then puts the item back, the system can lose sight of this item because of a changed location. In addition, you’ll hardly find alcohol in such a store because alcohol sales require shopper age identification.
AI improvement and education efforts may take a long time before innovators can introduce new generation stores operating without cashiers or other personnel. To address this challenge to a certain degree, we have developed an unusual motion detection (UMD) solution to identify shoppers’ atypical behavior. Here, the first implementation stage is all about UMD solution continuous learning based on real-life customer data, taking up to two weeks. The system collects data from video cameras and, after learning, can quickly detect atypical behaviors: a person is running instead of walking, stops where shoppers usually do not stop, zips a coat too slowly, carries a big backpack in his hand, or wears baggy clothes.
Another challenge for RPA adoption in the retail sector relates to vulnerabilities and hacking attempts – something both competitors and tech-savvy cybercriminals may exploit or opt for. Moreover, any Internet-connected system is exposed to DDoS attacks. Yes, it is. And robots as any artificial Intelligence tools, are exposed too. Modern RPA systems employ advanced security technologies resulting from an ever-lasting competition between cybercriminals and corporate white hats. Furthermore, when it comes to software robots, they are made fault-tolerant and definitely have proper and reliable protection, thus being a good choice for any retailer. Opportunities always go hand in hand with risks and it is an innovator’s responsibility to prudently assess such risk-to-opportunity balance and adopt the best possible approach using verified data and battle-proven technology.
In this infographic you will find the best statistics about artificial intelligence in the Middle East and find some quality insights for your business.
A health, safety & environmental (HSE) training in virtual environment helps employees address sophisticated issues in a more effective way, ensures maximum involvement in the production process, and allows for emergency drills being difficult to conduct in reality.
Should it be high voltage equipment failure or fire at the production facility, VR safety training helps reveal employee reaction to any emergency or sudden obstacles, reproduce tricky situations when an incident doesn’t follow the usual scenario, and, more importantly, enables employees to get prepared to such incidents in advance. For example, the introduction of VR in Ford’s manufacturing process reduced injures by 70%.
VR TRAINING
VR training is a virtual reality app developed in line with an emergency response procedure and staff training methodology as prepared by the specialists of the customer’s training center. During such VR trainings, employees obtain necessary knowledge and skills and pass tests in a computer simulation, with the test results being available for the supervisor who thus can speed up onboarding and new knowledge perception through practice.
Any hazardous situation or emergency, such as accidents on electrical distribution networks, can be easily reproduced in a computer simulation, with virtual reality technologies being capable of showing almost any content, including even “playback” of past accidents to prevent them in the future.
The consequences of any HSE breach can be reinforced in virtual reality through visual effects, like a full-screen explosion accompanied by bruising, thus impacting psycho-emotional state of employees to make them be more careful in their routine activities.
VR TRAINING FORMATS
VR training formats may differ depending on a particular task, each having certain advantages and limitations.
VR trainings can be tailored to various platforms: PC, VR glasses and headsets, industrial VR systems or multi-user devices with VR support. Each scenario differs in terms of user immersion, content adaptability for mobile use, and the quality of graphics.
Augmented reality 3D apps for smartphones and tablets can be used almost anywhere; however, the mobility advantage is balanced by rather poor quality of graphics.
Training on desktops (PCs) and laptops boasts the highest possible quality of graphics with an average level of immersion and mobility and is the most common format used by corporate training centers today.
VR tools are usually divided into:
Each format has its advantages and limitations. Thus, mobile VR has a high level of mobility, as users need just a smartphone or VR glasses themselves, and a high degree of immersion, since employee’s peripheral vision is not distracted. Both elements easily fit in a backpack, medium-sized bag or a classic briefcase. As a result, coaches are not tied to a specific training location and can easily conduct field demonstrations almost anywhere.
However, VR glasses do not support physical movement, with all content being perceived just from one point in a 360-degree format.
VR systems (HMD) offer the best possible graphics and the ability to move within a space of nine square meters, thus making it possible to get oneself truly immersed into virtual reality and interact with the surrounding virtual space using joysticks.
This format can be considered mobile as well because the equipment itself does not take much space and is not very heavy, but installation and configuration takes time and effort. This tool is perfect for classrooms at corporate training centers. In addition, a multiplayer solution is available for collective training where users can see avatars of each other, communicate and perform collective actions in a virtual world, thus achieving the maximum degree of immersion.
Is there a way to make sure that workers actually wear and use personal protective equipment (PPE) at hazardous production facilities? No big deal. Just train a neural network to recognize if PPE is on workers all over the facility, and then prevent accidents. How to do so? That’s what our today’s post is about.
Is standard CCTV system effective? There are ordinary people behind the cameras, getting tired, distracted, having momentary lapses in concentration that could prove fatal for workshop personnel. The good news is that progress comes to save the day. A properly trained artificial intelligence detects safety practice violations at once and in no time alerts a worker, one way or another, e.g. with a sharp sound, vibration, or SMS.
We trained AI-based video analytics to monitor safety compliance in the workplace in multiple ways:
We called this platform for workplace accident prevention “Digital Worker“, and its video analytics tool can detect:
How does a Digital Worker IoT platform count people and know a worker’s job? It does so by means of digital differentiation, capable of seeing the color of safety wear or hard hat on a worker as one of the ways. Let’s take a drilling site for example, where each hard hat color depends on the job. Blue hard hats are worn by drilling engineers, green is found on heads of drilling supervisors, and so on. The site can have color video cameras. The number of hard hats counted in real time is equal to the number of workers. Each camera covers a specific area of a drilling site. At the end of the day, all this data is consolidated to make a schedule for every area, showing what workers did the job, how many of them and in what area.
The system recognizes dangerous situations and notifies the operator about them. So, it is forbidden to be near the drilling rig when it is in working condition. In case a worker comes closer to the forbidden area, camera notices it and sends an alert.
The system also reacts when foreign objects prevent machinery operation. This picture shows how an animal is detected on the production line:
Can you trick a neural network? Let’s say, a worker fastens a hard hat to a belt. What is going to happen? In the case like this, two detectors are involved to find a bone structure, check whether a color spot is on top of it, and look for objects that move in sync. Therefore, a hard hat on the belt will hardly “look around” a person, because to do so, it should be on the head that moves in a certain way. Such a move can be easily detected, so tricksters are caught on their way to break rules.
What else can a neural network see?
Digital Worker platform is a mix of IoT and AI technologies and tools for industrial enterprises and construction companies developed to ensure employee safety and improve performance with a focus on minimizing the number of accidents, preventing fraud and safety violations.
