Just noticed the Gartner’s Magic Quadrant for Indoor Location Services, 2019 and one thing glared at me, again. Vacancy in the leadership QUADRANT. It was like this in 2018 too!
By 2022, 65% of enterprises will require indoor location asset tracking (both people and equipment) to be part of all access layer infrastructure communication decisions (up from less than 10% today) and yet there is no LEADER. Or, shall I say there is clear OPPORTUNITY.
The real challenge is that no one has yet definitively cracked the code on how to make adoption easy. Google, Apple, Microsoft … they all see the indoor space as the next BIG frontier but there is no one that can help with BLUE DOT easy.
The struggle starts from the moment you start looking to install the RTLS infrastructure. Whether the use is way finding, proximity services, personalized experience or asset tracking—maximizing the value of a solution requires a pervasive deployment.
How will you power all the RTLS receivers or Transmitters?
How will you install cables everywhere?
If you decide to use Battery based RTLS receivers/transmitters than you will end up doing significant battery management. Periodically changing batteries by going from receiver to receiver (or transmitter to transmitter) in person, finding and replacing a malfunctioning receiver (transmitter), changing parameters, or security updates – nothing is easy. With batteries, you also end up establishing processes for re-charging, storing, and disposing of the batteries you’ll use.
Many Wi-Fi companies added BLE (Bluetooth low energy support) in their Wi-Fi Access Points so that the access points can act as iBeacon transmitters as well as BLE receivers to alleviate the need of additional battery or installations. This is a step in the right direction indeed, however, the location accuracy is “limited”. Furthermore, these solutions require additional access points from same vendor or need to be augmented by battery based solutions. Recent AI based solutions such as https://www.themarysue.com/wifi-positioning-system-mit/ suffer from accuracy too.
There’s an untapped universe of data around physical locations that businesses can utilize and the right approach can transform real-time location-based services across retail, hospitality, healthcare, industrial and many more industries.
Neural Networks for Route Management for Driverless Car Fleet
Managing a fleet of autonomous vehicles for the purpose of mobility-as-a-service – competing with likes of Uber or Black cab, poses another set of challenges beyond the singleton self-driving car. In this session, we will discuss how artificial neural networks will play a critical role in fleet management operations such as route computation.
Big data, machine learning, and security needs are requiring computers to be infinitely faster, have infinite amounts of storage, and have infinite security capabilities. And this is happening on the heels of the slowdown of Moore’s Law. In five years, the needs for traditional compute functionality in the cloud will be so large that it can never be built. Thankfully, quantum computing has arrived, and it promises to revolutionize the cloud. What quantum computing provides is massively parallel processing, atomic-level storage, and security using the laws of physics rather than external cryptographic methods.
In this session, you will learn:
Exactly what quantum computing is
The essential role quantum computing will play in the cloud
How quantum computing makes machine learning possible
What quantum computing means for businesses and IT leaders
When: 9:40 AM – 10:20 AM, Room 201, April 02, 2018
If not registered yet, please register as attendee.
AI is the key to unlock IoT potential
Without AI, data from the IOT deployments has “limited value” as traditional business intelligence tools can’t wring insights from data quickly enough. If your company has plans for building or implementing IoT-based solutions, those plans should probably include AI as well. In this session you will learn how AI can help companies avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.
Former Head of Architecture/Engineering of Worldwide Corporate Network at Google, Ajay is a technologist, business futurist, & prolific inventor with about 90 patents pending/issued specializing in artificial intelligence, Wi-Fi networking, Quantum computing, and Real Time Location. He is author of “RTLS for Dummies”, “Augmented Reality for Dummies” & “Artificial Intelligence for Wireless Networking”.
Ajay Malik is currently CTO & Head of Engineering of Lunera, an IOT infrastructure company, and responsible for creating the vision for the company; lead the technology development to realize this vision and evangelize the technical approach. Ajay joined Lunera from Google, where he was head of architecture and engineering for the worldwide corporate network. Prior to Google, Ajay was senior vice president of engineering and products at Meru Networks where he led the transformation of the company’s technology resulting in its acquisition by Fortinet. Ajay has also held executive leadership positions at Hewlett-Packard, Cisco, and Motorola. He completed B.E in Computer Science & Technology from IIT, Roorkee, India, one of the premier institutes of India.
Wi-Fi has moved from a nascent technology to one that is core enabler of digitalized user experience. It is at center of Internet of Things (IoT), virtual reality (VR), augmented reality (AR), real-time location systems (RTLS), and smart devices, to name just a few. And yet, even after years of evolution and innovation, wireless networks today require hands and heads. There is a need for an autonomic wireless management system that “watches” the network, “understands” normal functioning, “analyzes” real-time performance against norms, and then “acts” to automatically solve known problems. This is where machine learning and artificial intelligence come in. In this session, you’ll learn why it’s likely that future Wi-Fi networks will be completely dominated by AI. You’ll also find out what the artificial intelligence-enabled Wi-Fi network of tomorrow will look like and how AI will help in delivering richer and differentiated user experiences, security, and more.