Internet of Things (IoT)
IoT, or the internet of things, refers to physical objects with appropriate software systems, sensors, processing abilities, and other technologies that can seamlessly connect with other devices to exchange data and information over the communications networks or the internet. IoT is the essential technology that helps in hassle-free communication between companies, people, things, and processes. Recent advances like faster connectivity, cloud computing platforms, low-cost, low-power sensors, conversational artificial intelligence, machine learning and analytics, etc., are some of the technologies that make IoT a successful reality.
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How to avoid unnecessary wastage of money on IoT?
Focus on targeting the high-value business outcomes. To save more, ensure that the solutions are sustainable. Proper incorporation of resources can help devise appropriate solutions that can reliably work for years. Also, companies need to develop a specific mindset that allows users to identify the issues that need an answer, not any IoT idea that constantly looks for a problem.
What is a business outcome and insight in IoT?
Insight determines the overall business outcome for a company. If you already have proper insights about the problem, it gets easier to devise the right plan of action using IoT. For example, having insight means knowing that a device might break down and lose data if not adequately cared for at the right time. Using this information, it gets simpler to resolve the problem by scheduling the repair as soon as possible. So, insight is just part of solving a business problem.
How does AI fit into IoT?
AI and ML both play significant roles in IoT. ML can help in yielding insights from the difficult-to-handle stored data. Using machine learning calculations, the system gradually learns to solve problems using the tools available in the cloud or the enterprise's data center. After this, the learning is deployed to the inferencing engine at the edge for running in real-time. IoT offers data, while AI is responsible for acquiring the power for unlocking the responses. Overall, both together offer context and creativity to drive more intelligent actions. AI in IoT helps in achieving agile solutions like:
- Analyze, manage, and procure meaningful insights from collected data
- Ensure speedy and accurate analysis
- Maintain security against potential cyber attacks
- Balance personalization with data privacy and confidentiality
- Balance requirements for localized as well as a centralized intelligence
How does data science work with IoT?
Data science finds its place in helping extract insights from collected data systematically. It allows businesses to create solutions for achieving growth and reducing operational expenses. Here, IoT plays a crucial role by offering its real-time capabilities. So, IoT can change the dynamics of data analysis with its real-time sensor readings from smart gadgets. As a result, it helps the data science experts instantly create accurate evaluations.
Is it mandatory to use edge with IoT?
Data processing happening at the data source is your key. Local insights are valuable for obtaining quick local action and data that need not be transported. Writing the simple applications within the edge compute system is hassle-free and easy, as the resources are solely dedicated to the task alone. As a result, getting the solution production-ready gets simpler.
Should security be a significant concern with IoT?
Security should be a great concern as IoT offers a large attack surface. A substantial number of devices are prone to theft and security issues as scammers and hackers target them for breaking into them to misuse their computational capabilities. Whether large or small attacks, the security of IoT devices will always be of utmost concern.
Does big data analytics help in IoT?
Big data analytics govern the growth and evolution of IoT. Therefore, it is crucial for the effective functioning of IoT. In simpler terms, big data acts as the fuel of IoT while AI drives the connected things while playing the role of a brain. So, in the case of IoT, the real value is derived from driving intelligent insights, thereby making smarter connected things that can eventually pave the way for new ventures and businesses.
Are digitization and IoT similar concepts?
IoT strictly refers to the aspect of digitization where it uses data analytics to drive a business. However, these terms are generally used interchangeably.
State the diverse applications of IoT
The critical applications of IoT can be found in different sectors like smart homes, industrial automation, healthcare sectors, automotive, and wearable technology. Here are some examples:
- A home security camera is known for recording and detecting changes while sending alerts to the connected smartphone
- Elevator-monitoring systems that track proper functioning for making scheduled maintenance at convenient time intervals
- Hospital patient monitoring
- Identifying earthquakes
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