Data is crucial for organizations to drill down and generate actionable insights. It is estimated that 99.5% of digital data is not even analyzed. The ever increasing flow of data from both humans and Internet of Things (IoT) devices will only continue to grow. Enterprises can meet the data challenge only by gaining a "cognitive advantage". In the coming years, Artificial Intelligence (AI) is a ‘must have’ to stay competitive. Our latest thinking encapsulates why AI-enabled IoT remains the key to business success in the digital age.
Very soon, it will be extremely hard to find an Internet of Things (IoT) implementation that does not make some use of Artificial Intelligence (AI). A recent study by the International Data Corporation (IDC) reveals that by 2019, 100% of all effective IoT efforts will be supported by cognitive or AI capabilities. The key: unlocking insights hidden in data. The huge volumes of data gushing from numerous IoT devices have limited value without AI technologies that are capable of finding valuable insights in the data.
A case in point: "Tesla, the household name in the electric car market, is a pioneer to use AI and IoT, and unleash a revolution in the autonomous, self-driving car manufacturing industry. All Tesla vehicles and its drivers have internal or external sensors integrated to their parts, that continuously send data to the cloud. Machine learning feature in the cloud in turn educates their entire fleet of cars, which helps in addressing a wide range of requirements, including any software or hardware repairs on the vehicle, locating spots of hazards, managing traffic speed, receiving alerts from road sensors, forewarning drivers, and so on. Taking a step forward, Tesla has started to experiment on interacting with the interfaces of other car manufacturers, such as exchanging data through integrated sensors, and processing the data using AI systems, with minimal human effort. In short, Tesla effectively uses IoT to crowdsource its data from all of its vehicles and uses AI to train itself".
The call is clear, "AI is the future of IoT".
Integrating AI has become a pre-requisite for success in today’s IoT-based digital ecosystems. AI will rewrite the strategies of virtually every industry, as it helps in building ‘smart or cognitive systems’ that require little or no human intervention to take informed decisions.
The past two years witnessed companies acquiring a plenty of firms that work at the intersection of AI and IoT. Many of the leading IoT platform vendors (such as Amazon, IBM, Oracle, Microsoft etc.) started offering integrated AI capabilities such as machine learning-based analytics. The principal reason behind AI holding the reins in enterprises is its ability to churn insights quickly from bulk quantities of data. Besides insights generation, the powerful combination of AI and IoT enables companies to avoid unplanned downtime, increase operational efficiency, enable new products and services, and improve risk management capacity.
Cognitive computing techniques such as face detection and recognition, natural language processing, and character recognition technology transform the way organizations derive value out of data. While IoT accelerates and sustains the growth of data in enormous quantities, the application of AI makes the data more actionable. In other words, the convergence of AI and IoT augments "connected intelligence".
|AI influencing IoT in two ways||1.Enabling real-time responses||2.Post-event processing support|
|Imagine a face recognition and analytics software deployed on an embedded robotic platform. The data collected by the image sensors on that robot are used to recognize who is in the image, where they are located within the image, or to define unique attributes of specific people in the image.||The analytics derived from remote video cameras that read characters on license plates or analyze faces can be used for understanding patterns over time, and decide the course of future action.|
The fusion of IoT and AI is empowering B2B firms to improve their value proposition. The intersection enables enterprises to create more adaptive learning systems, since other technologies offer only minimal support to this type of advanced (cognitive) analytics.
Technology has drastically improved patient experience and enhanced caregiving.
Harman, a leading provider of audio, video, lighting and control systems for global enterprises has collaborated with IBM Watson IoT to address the problem of patient engagement, by building cognitive hospital rooms. This intelligent, adaptable solution based on IoT and cognitive computing, is making the lives of patients, guests and healthcare professionals easier.
Smart body sensors can be used to gauge bodily activities, pulse rates, body postures and other metrics to enhance safety and health of people, while medical sensors alert caregivers on varying blood sugar levels, and dispense insulin, if required. Using AI to train health monitoring systems can help professionals to keep track of their patients’ activity levels, help them improve their behavior and support overall health management.
A common example of the advent of IoT and AI in the travel and leisure business is the introduction of chatbots. If programmed specifically, AI provides these systems the ability to respond to customer queries and requests, without the need to talk to a live travel agent. AI-enabled IoT gives us the power to dive inside things, automate and streamline processes and transform the entire travel experience.
A leading example is the London City Airport, the first one of its kind to use cross-technology networking for improving passenger experience and running operations in a secured environment. Connected IoT devices enable airlines crew to track passengers’ journey through the terminal, predict exigencies, alert boarding gate staff before big queues line up, let passengers know when to set off from gate transfer trains, ready coffee orders to be served for ticket holders at boarding points, and above all speed up the security and baggage check-in process, and track missing luggage or lost passengers.
In short, AI and IoT can build an intelligent and integrated relationship management system in the travel and leisure industry.
The recent years have witnessed retailers of different scales investing amply in retail tech and innovation to enhance their businesses and provide better service to their customers.
A case in point is the Walmart model, that combines the best of both worlds, with more than 11,000 brick and mortar outlets as well as online stores that meet the sales demand and customer demand equally. Walmart uses Machine Learning, AI, IoT and Big Data to boost its retail performance. It uses facial recognition technology to keep track of customer identities and their shopping patterns, integrates IoT tags to monitor product details, employs machine learning skills to optimize home delivery routes, and now, has introduced voice based search powered by Google Assistant.
Gartner estimates that by 2020, 85% of customer-enterprise relations will not involve human interaction. Through cross-technology solutions, modern day retailers are able to establish a highly engaging and personalized online shopping experience.
In reality, Internet of Things (IoT) has been doing its rounds in logistics, warehouses and supply chain in for many years. Not to forget the asset tracking applications where RFID and IoT are present as part of end-to-end inventory management. DHL, the global logistics provider suggests the application of AI and IoT for logistics optimization. Big data analytics and machine learning transform the processes of manufacturing, logistics, transportation and warehousing by making them increasingly efficient, productive, and profitable.
AI and IoT do not just limit their operations to backend systems and processes. Transportation firms could use AI and IoT to proactively respond to maintenance issues by mitigating costly repairs and downtime, alerting maintenance staff and keeping passengers and freight safe. This increases the value of vehicle lifetime and decreases their insurance-related costs. Recently, the retail giant Amazon has started testing out robots in its warehouses to increase productivity and perform quality checks.
The possibilities of creating driverless trucks and completely automated truck fleets are not far away.
Unlike other verticals, physical security industry is a domain that craves for more technological advances, but is rather slow in the rate of technology adoption. However, the customer demand for advanced physical security systems is on the rise. MarketsandMarkets research firm predicts that by 2021, the physical security market will reach $113 billion which was only $70 billion in 2016. Another emerging trend in the industry is that many customers prefer a combination of physical security systems and internet security systems, which will make the product highly adoptable for both home and business users.
While adoption of IoT ensures well- connected security systems, embedding of cognitive/ AI capabilities reinforces the security locks. Integration of super-human facial recognition systems and biometric access devices facilitate remote monitoring of physical security. A case in point is Zicom Electronic Security Systems that uses IoT to build a connected platform for electronic surveillance of business premises such as banks, ATMs and financial institutions. Zicom also uses AI to build home security cameras that makes use of voice. Many banks were able to bring down their security expenses considerably using AI-powered IoT security systems.
AI and IoT empower organizations with customized analytics that can be used to create personalized security warnings and ‘trigger’ requirements.
Intelligence and connectivity powered by AI and IoT inculcate an entirely new set of product functions and capabilities, that can be broadly grouped into four areas: monitoring, control, optimization and autonomy. These milestones help businesses to define their competitive positioning.
In short, IoT enabled by AI will help businesses to:
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