Tag Archives: Big Data

AIoT: How the Intersection of AI and IoT Will Drive Innovation for Decades to Come

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We have covered the evolution of the Internet of Things (IoT) and Artificial Intelligence (AI) over the years as they have gained prominence. IoT devices collect a massive amount of data. Cisco projects by the end of 2021, IoT devices will collect over 800 zettabytes of data per year. Meanwhile, AI algorithms can parse through big data and teach themselves to analyze and identify patterns to make predictions. Both technologies enable a seemingly endless amount of applications retained a massive impact on many industry verticals.

What happens when you merge them? The result is aptly named the AIoT (Artificial Intelligence of Things) and it will take IoT devices to the next level.

WHAT IS AIOT?

AIoT is any system that integrates AI technologies with IoT infrastructure, enhancing efficiency, human-machine interactions, data management and analytics.

IoT enables devices to collect, store, and analyze big data. Device operators and field engineers typically control devices. AI enhances IoT’s existing systems, enabling them to take the next step to determine and take the appropriate action based on the analysis of the data.

By embedding AI into infrastructure components, including programs, chipsets, and edge computing, AIoT enables intelligent, connected systems to learn, self-correct and self-diagnose potential issues.

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One common example comes in the surveillance field. Surveillance camera can be used as an image sensor, sending every frame to an IoT system which analyzes the feed for certain objects. AI can analyze the frame and only send frames when it detects a specific object—significantly speeding up the process while reducing the amount of data generated since irrelevant frames are excluded.

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While AIoT will no doubt find a variety of applications across industries, the three segments we expect to see the most impact on are wearables, smart cities, and retail.

WEARABLES

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The global wearable device market is estimated to hit more than $87 billion by 2022. AI applications on wearable devices such as smartwatches pose a number of potential applications, particularly in the healthtech sector.

Researchers in Taiwan have been studying the potential for an AIoT wearable system for electrocardiogram (ECG) analysis and cardiac disease detection. The system would integrate a wearable IoT-based system with an AI platform for cardiac disease detection. The wearable collects real-time health data and stores it in a cloud where an AI algorithm detects disease with an average of 94% accuracy. Currently, Apple Watch Series 4 or later includes an ECG app which captures symptoms of irregular, rapid or skipped heartbeats.

Although this device is still in development, we expect to see more coming out of the wearables segment as 5G enables more robust cloud-based processing power, taking the pressure off the devices themselves.

SMART CITIES

We’ve previously explored the future of smart cities in our blog series A Smarter World. With cities eager to invest in improving public safety, transport, and energy efficiency, AIoT will drive innovation in the smart city space.

There are a number of potential applications for AIoT in smart cities. AIoT’s ability to analyze data and act opens up a number of possibilities for optimizing energy consumption for IoT systems. Smart streetlights and energy grids can analyze data to reduce wasted energy without inconveniencing citizens.

Some smart cities have already adopted AIoT applications in the transportation space. New Delhi, which boasts some of the worst traffic in the world, features an Intelligent Transport Management System (ITMS) which makes real-time dynamic decisions on traffic flows to accelerate traffic.

RETAIL

AIoT has the potential to enhance the retail shopping experience with digital augmentation. The same smart cameras we referenced earlier are being used to detect shoplifters. Walmart recently confirmed it has installed smart security cameras in over 1,000 stores.

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One of the big innovations for AIoT involves smart shopping carts. Grocery stores in both Canada and the United States are experimenting with high-tech shopping carts, including one from Caper which uses image recognition and built-in sensors to determine what a person puts into the shopping cart.

The potential for smart shopping carts is vast—these carts will be able to inform customers of deals and promotion, recommend products based on their buying decisions, enable them to view an itemized list of their current purchases, and incorporate indoor navigation to lead them to their desired items.

A smart shopping cart company called IMAGR recently raised $14 million in a pre-Series A funding round, pointing toward a bright future for smart shopping carts.

CONCLUSION

AIoT represents the intersection of AI, IoT, 5G, and big data. 5G enables the cloud processing power for IoT devices to employ AI algorithms to analyze big data to determine and enact action items. These technologies are all relatively young, and as they continue to grow, they will empower innovators to build a smarter future for our world.

A Smarter World Part 3: How Smart Transportation Will Accelerate Your Business

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In the last installment of our blog series on smart cities, we examined how smart infrastructure will revolutionize smart cities. This week, we will examine the many applications which will soon revolutionize smart transportation.

A smarter world means a faster, more efficient and environmentally-friendly world. And perhaps the biggest increase in efficiency and productivity will be driven by the many ways in which AI can optimize the amount of time it takes to get where you’re going.

Here are the top applications in smart transportation coming to a city near you:

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AUTONOMOUS VEHICLES

Some say autonomous vehicles are headed to market by 2020. Others say it could take decades before they are on the road. One thing is for certain, they represent a major technological advancement for smart transportation. Autonomous cars will communicate with each other to avoid accidents and contain state-of-the-art sensors to help keep you and your vehicle safe from harm.

Although autonomous vehicles are arguably the largest technological advancement on the horizon, they will also benefit greatly from a variety of smart transportation applications that will accelerate navigating your local metropolis.

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SMART ROADS

What if we could turn roads into a true digital network, giving real-time traffic updates, supporting autonomous car technology, and providing true connectivity between vehicles and smart cities?

That’s the question tech start-up Integrated Roadways intends to answer. Integrated Roadways develops fiber-connected smart pavement outfitted with a vast amount of sensors, routers, and antennae that send information to data centers along the highway. They recently inked a 5 year deal to test out patented fiber-connected pavement in Colorado.

Smart Roads represent a major advancement in creating vehicle-to-infrastructure (V2I) connectivity. With 37,133 deaths from motor vehicles on American roads in 2017, the combination of AI applications in smart roads and autonomous cars could revolutionize vehicular transport and create a safer, faster world.

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SMART TRAFFIC LIGHTS

The vehicle-to-infrastructure connectivity spans beyond the roads and into the traffic light. Idling cars generate an estimated 30 million tons of carbon dioxide. Traffic jams can make it harder for first responders to reach emergencies. Rapid Flow proposes that the answer may be their AI-based adaptive traffic management system called Surtrac.

Surtrac uses a decentralized network of smart traffic lights equipped with cameras, radar, and other sensors to manage traffic flows. Surtrac’s sensors identify approaching vehicles, calculate their speed and trajectory, and adjust a traffic signal’s timing schedule as needed.

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SMART PUBLIC TRANSIT

There are a variety of smart applications which are revolutionizing public transportation.

In Singapore, hundreds of cameras and sensors citywide analyze traffic congestion and crowd density, enabling government officials to reroute buses at rush hour, reducing the risk of traffic jams. In Indianapolis, the electric Red Line bus service runs a 13 mile path that travels within a quarter of a mile of roughly 150,000 jobs.

One of the major disruptors which has seen rapid adoption in the smart public transport are electric scooter sharing services like Bird and Lime. Electric scooters fill in the public transportation gap for people looking to go 1-3 miles without having to walk or take a taxi. Electric scooters have seen adoption in Los Angeles, San Francisco, Salt Lake City, Brooklyn, and more cities around the globe.

CONCLUSION

Smart cities will have a host of revolutionary applications working in unison and communicating through smart infrastructure with municipalities to ensure maximum efficiency and safety when it comes to transportation. In our next installment of our series on smart cities, we’ll examine how smart security will help keep city-dwellers safe.

A Smarter World Part 2: How Smart Infrastructure Will Reshape Your City

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Imagine a city that monitors its own health, identifies potential fail points using AI algorithms, and autonomously takes action to prevent future disasters.

This is the smart-city of the future. In our first installment of our blog series on Smart Cities, we ran through an overview of how Smart Cities will change our world. In this second entry of our blog on smart cities, we’ll examine perhaps the biggest building block necessary to create a smart city: smart infrastructure.

The construction of a smart city begins with developing a vast, city-wide IoT system, embedding sensors and actuators into the infrastructure of the city to create a network of smart things. The sensors and actuators collect data and send it to field gateways which preprocess and filter data before transmitting it through a cloud gateway to a Data Lake. The Data Lake stores a vast amount of data in its raw state. Gradually, data is extracted for meaningful insights and sent to the Big Data warehouse where it’s structured. From here, monitoring and basic analytics will occur to determine potential fail points and preventative measures.

Check out the breakdown below:

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As you can see, it all begins with the construction of smart infrastructure that can collect data. Here are some of the big applications in the smart infrastructure space:

STRUCTURAL HEALTH

One of the major applications of smart infrastructure will be monitoring key data points in major structures, such as the vibrations and material conditions of buildings, bridges, historical monuments, roads, etc.

Cultivating data will initiate basic analysis and preventative measures, but as we gather more and more data, AI and machine learning algorithms will learn from vast statistical analysis and be able to analyze historical sensor data to identify trends and create predictive models to prevent future disasters from happening with unprecedented accuracy.

Learn more about how Acellant is building the future of structure health monitoring.

ENVIRONMENTAL APPLICATIONS

There are a multitude of potentially environmental applications for smart infrastructure designed to optimize city activities for environmental health. For example, embedding street lights with intelligent and weather adaptive lighting will reduce the amount of energy necessary to keep roads alight.

Air pollution monitoring will help control CO2 emissions of factories and monitor the pollution emitted by cars. Ultimately, earthquake early detection can help monitor distributed control in specific places of tremors.

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WASTE MANAGEMENT

Boston is well-known as one of the top college cities in the United States. Every fall, over 160,000 college students from MIT, Harvard, Northeastern, BU, BC, Berklee School of Music, and more move in to their new living spaces, causing undue stress on the city’s waste management administration. ANALYZE BOSTON, the city’s open data portal, provided key data points such as housing rentals, trash volume and pick-up frequency, enabling a project called TRASH CITY to reroute waste management routes during this trying time.

CONCLUSION

Projects like Trash City show the many ways in which we can optimize city operations by analyzing data effectively. As smart infrastructure enables the collection of more and more data, projects like TRASH CITY will become more efficient and more effective.

Of course, the biggest application of Smart Infrastructure will be the many ways in which it will change how you get from A to B. Next week, we’ll focus in on smart transportation and how it will reshape metropolitan transportation.