AIoT – Implementing AI to IoT Data

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Have you ever wondered how everything is becoming so smart? How are gadgets able to make human-like decisions? The answer to all these wonders is hidden in the buzzwords AI (Artificial Intelligence) and IoT(Internet-of-Things). Indeed, when blended, these are the highly innovative technologies resulting in the origin of even the most crucial technology (AIoT) that has immense potential to change the world drastically.

With such rapid advancements in technological progression, AIoT (Artificial intelligent of Things) is redefining and reforming every industry. AI paves the way for intelligent task execution with real-time analysis while IoT bridges the communication scale between devices. The merging of these two technologies makes each other’s applications more effective and powerful. While IoT serves the purpose of data collection and storage to the cloud, AI is regarded as the brain that essentially functions in decision making and stimulating the machines to respond.

Research and Markets predict that the global AIoT market will reach 65.9 billion dollars with a CAGR of 39.1% by 2025. The article aims to discuss how AI and IoT technologies are related and how they work cohesively to create immense value for different perspectives. This article sheds light on answering some of the following questions revolving around AIoT technology.

  • What is AIoT and why is it necessary?
  • How do Artificial Intelligent of Things enabled applications work?
  • What are the benefits of AIoT?
  • What are the use-cases of AIoT?

What is AIoT and why is it necessary?

AIoT involves embedding AI technology with different IoT components. Essentially, the combination of AI and IoT is one of the significant keys to accelerate technological development and services in the digital domain. Its objective is to rapidly increase operational efficiency, improve human-machine interactions, and even upgrade data management and analytics.

Here’s a quick rundown of the roles played by both technologies and how they develop a symbiotic relationship with each other.

  • Internet of Things (IoT)
    It refers to a system that extends the internet to various objects, sensors, and devices (things) to collect and share data from their environments with the help of other devices or software programs. IoT aims to connect machines and objects.
  • Artificial Intelligence (AI)
    Artificial Intelligence thrives on data. It is all about learning and automation using a range of statistical and computational techniques. It refers to a system capable of learning from data or performing tasks typically associated with intelligence similar to humans. AI technologies comprise machine learning (ML), natural language processing (NLP) and voice and face recognition. To be more precise, AI brings intelligence to machines and objects.

Together, the two technologies AI and IoT, create intelligent, connected systems, where AI functions as a brain to IoT’s body. The IoT devices collect and transmit data from multiple sources to support the learning process involved in AI to carry out automation.

AI brings machine-learning and decision-making power to IoT systems, thereby enhancing data management and analysis with massive productivity gains.

When combined with AI, IoT devices get additional capabilities like learning from user interactions, service providers, and other relevant devices in the network. They are adjustable to new inputs and changes in the environment and execute the tasks without any manual intervention.

How does Artificial Intelligent of Things-enabled devices work?

As IoT networks are increasing rapidly across every industry, an ample amount of unstructured machine data also exists. The rising amount of human-oriented and machine-generated information develops the need for AI support to handle unstructured data analytics. The data generated from IoT-supported systems is essential as it can serve corporate needs and solve the functional problems associated with product lifecycle management.

AI and IoT comprise similar interconnected components. When these two technology sets go hand-in-hand, they become mutually beneficial and add value to each other. AI adds value to IoT due to machine learning and decision-making processes while IoT adds value to AI due to data exchange, signaling and connectivity.

AIoT exhibits the need for interoperability of devices (chipsets), software (programs and operating systems) and platforms. As earlier AI implementations were monolithic with vertically designed solutions, they require APIs to make the devices, software and platforms highly interoperable.

Following are the sequential steps of any AIoT enabled solution.

workflow of aiot

Step 1: Data Collection

Data collection is an initial stage, where the data is collected using sensors. These sensors are installed in IoT devices. A single device may incorporate multiple sensors for managing the different types of data. It is possible to connect various sensors to a single device for collecting different kinds of data. For example, a device may include multiple sensors like GPS, camera, accelerometer for data collection.

Step 2: Data Transmission and Storage

Once the data is collected, it is further transmitted and stored in the cloud due to its high volume. Cloud storage minimizes the overall cost of storage because organizations don’t need to spend a tremendous amount on hardware installation for data storage. The stored data is further used for processing and analysis.

Step 3: Data Processing

The stored data in the cloud is used for processing. Data processing involves different phases like relevant data extraction from the cloud, data cleaning and making it anomalies free, data conversion into a standard format and applying algorithms for deriving insights.

Step 4: Data Prediction

After processing the data, the machine learning algorithms help in predicting future events. Once the relevant models are generated, it becomes easier to make predictions based on obtained results. For example, clustering models predict image patterns; anomaly detection models predict the possible faults, text-based models allow text classification and entity recognition.

Step 5: Actionable Insights

After making the predictions, the eventual step for machines is to take actions as per the generated insights. Insights and advanced dashboards assist in aligning business goals, fine-tune processes and creating future strategies. The data visualization tools like Tableauand Microsoft Power BI effectively visualize massive data having millions of data points. Data points and predictions help take real-time actions. For example, visual plotting is beneficial to create the reports in detail.

These steps describe the relevance of combining IoT with AI. While the IoT devices collect data from different resources, AI components acquire valuable insights from the collected data and act accordingly.

What are the benefits of Artificial Intelligent of Things?

benefits of aiot

AIoT provides numerous benefits to companies and consumers with an excellent personalized experience, proactive intervention and intelligent automation.

Boosting Operational Efficiency

AIoT deployment helps in streamlining the business operations with accurate predictions and improved efficiency. The machine learning tools coupled with AI predict the operational conditions and detect the parameters requiring modifications to ensure better outcomes. Besides providing constant data streams, identifying the patterns which are not deceptive on simple gauges, AIoT also delivers meaningful insights to avoid process redundancy and excessive time consumption. For example, Google leverages the power of AIoT for minimizing its data centers’ cooling costs.

Advanced Risk Management

The combination of AI and IoT assists in predicting the possible risks and automated rapid response. It results in handling financial losses, employee safety and cyber threats. For example, Fujitsu helps ensure the safety of workers with the analysis of data sources by AI and the connected wearables.

Elimination of costly unplanned downtime

Various organizations like oil and gas industries usually suffer from unplanned breakdowns. The equipment breakdown imposes downtime that incurs heavy losses. Having the combined AI-enabled IoT platform and devices helps monitor machines consistently and identify the patterns for predicting machine failures well in time. The prior prediction of equipment loss helps to schedule the orderly maintenance procedures. AIoT devices assist in anticipating machinery failures and breakdown by using data analytics and preventing downtime’s side effects.

Enhanced Products and services

Natural Language Processing aims to improve communication through speech, text or gestures between humans and devices. AIoT can directly create new products and enhance existing services’ quick data analysis and processing for businesses. AIoT-powered devices like robots and drones offer a complete sense of inspection and monitoring to make human-like intelligent decisions and take proper actions. For commercial vehicles, it helps in fleet management by monitoring every measurable information. Rolls Royce is a great example that uses AI into IoT-enabled airplane engine maintenance to spot perceptual patterns and explore operational insights.

High scalability

IoT devices range from high-end computers to microsensors and chipsets. A standard IoT system comprises battery-powered sensors for managing the vast volume of data. AI plays a vital role in identifying, summarising and scrutinizing the enormous data flow on cloud storage. As the high volume of data becomes manageable, it ultimately improves the scalability of the entire IoT ecosystem.

What are the use-cases of AIoT?

AIoT has a wide range of use-cases for almost every industry with different perspectives. Some of them are stated below. Most of the use-cases of AIoT are in demand for streamlining operational processes, downtime prevention and an ample amount of data management.

Robotics

Most of the industrial sector like manufacturing has a great need to adopt AI-powered IoT solutions. These solutions resulted in facial recognition, deep learning, big data analytics and the emergence of robots. Robots employed in factories enhance the manufacturing process with excellent efficiency, brilliant work and reliability. The sole reason behind the intellectual functioning of robots is the implanted sensors that facilitate data transmission and thorough communication. Apart from learning and adapting to a new environment, AIoT powered robots make the manufacturing process linear with the savage of time and money. 

Traffic Monitoring and Management

Traffic Management is crucial in urban areas to avoid congestion and chaos. The practical uses of AIoT based solutions like drones help to monitor real-time traffic. When drones are deployed to supervise a large area, they transmit traffic data. Then AI analyzes the data to make decisions for alleviating traffic congestion with speed limits and timing adjustments of traffic lights without any human intervention.For example, ET City Brain is a product developed by Alibaba Cloud that optimizes the use of urban resources with the help of AIoT. This system detects accidents, illegal parking areas and alters the traffic lights to help ambulances get to patients requiring quick assistance.

Body Sensors / Wearables

Maintaining good health is a tough challenge and the need of the hour. With the Coronavirus pandemic, everyone has become extra cautious with their health and the technologies like AI and IoT are leveraging the entire healthcare sector. Visiting doctors frequently for regular checkups is difficult for a large population. This problem is solved with wearable devices like fitness trackers, smartwatches, panic buttons to track blood sugar level, cholesterol level, etc.The Healthcare Industry needs to deal with vast data and IoT adds a significant volume with wearable devices. AI offers meaningful insights into the data and assists in real-time responses, HR management, inventory management, allied pharmacy services. AIoT applications help collect data to provide preventive measures for a person, early detection, and drug administration.

Retail Analytics

Staff management is of prime importance in retail outlets. The sensors powered with AIoT can trace the people entering the outlets and their activity to estimate their time to reach the checkout line. According to this analysis, the number of staff at the counter can be increased or decreased to reduce checkout time and enhance productivity.

Fleet management and Self-driving vehicles

AIoT is used in fleet management today to monitor a fleet’s vehicles, reduce fuel costs, track vehicle maintenance, and identify unsafe driver behavior. The powerful AIoT equipped sensors, installed cameras, robust software and hardware integration enables self-driving vehicles to make human-like decisions. For example, Tesla’s self-driving cars can determine the weather and road conditions, alternative routes, optimal speed, and predict pedestrians’ behavior in various circumstances.

Smart Buildings, Cities and Industries

Apart from homes, a whole building, city and an entire industry can have AIoT installed for better operational efficiency and cost management. A network of AIoT devices in buildings detects the presence of personnel and adjusts the temperature accordingly with the savage of energy and cost.The factors like smart traffic management, smart parking, smart waste management, smart governance constitute a smart city. The integration of AI and IoT changes the way cities operate and delivers amenities to the public, including transportation, healthcare, water and waste management, drainage systems, electric grids, road and rail management, safety and security aspects, etc.

Smart Industry devices powered with AIoT use real-time data analytics and machine-to-machine sensors to optimize operations, logistics and supply chain. The data captured with these AIoT devices assist the industries in foreseeing challenges by avoiding errors and workplace injuries.

The fusion of AI and IoT is a breakthrough leading towards the smart revolution. Apart from causing a fundamental shift, companies have been given a competitive advantage and contribute to cost-effective alternatives. Alone, AI and IoT are limited, but the technology can do wonders when they come together. Both IoT and AI are powerful and are capable of making every aspect brighter.

Combining these two technologies will enable enterprises to achieve even more remarkable digital transformation. There are tons of domains that can harvest the advantages of the coexistence of both technologies. AIoT technology has a significant impact on every business segment to maximize profit, function more efficiently and facilitate the creation of a connected, innovative, and intelligent world.

LeewayHertz has been at the forefront of this smart revolution, helping numerous enterprises to build AIoT enabled solutions. To know more on how to truly unlock the potential of IoT and AI technologies, share your details with us and contact our experts for a detailed consultation session.

Author’s Bio

Akash Takyar
Akash Takyar
CEO LeewayHertz
Akash Takyar is the founder and CEO at LeewayHertz. With the experience of building over 100+ platforms for startups and enterprise allows Akash to rapidly architect and design solutions that are scalable and beautiful.
Akash's ability to build enterprise-grade technology solutions has attracted over 30 Fortune 500 companies, including Siemens, 3M, P&G and Hershey’s. Akash is an early adopter of new technology, a passionate technology enthusiast, and an investor in AI and IoT startups.
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