The Implementation of AI & ML in IoT Apps
Artificial Intelligence, known as AI, and the internet of things, known as IoT are the key contributors in all major industries in the world. The adoption of AI and IoT is considered to be a great investment and powerful acquisitions for any kind of company. As AI drives advancements in data collection, analysis& processing, and IoT provides connectivity, and smart devices to ease up any process.
AIML & IoT go hand in hand in building the most powerful digital solutions and solve the toughest business challenges.
Business challenges solved by implementing AIML and IoT technologies
The value of AI is in its ability to analyze data, automatically identify anomalies in generated insights adding to that it can provide operational predictions with great accuracy.
Combined with IoT, AI technologies implemented in digital solutions such as speech recognition and computer vision, work on extracting useful insight and conclusions from data that used to be exposed to “human mistakes” for review. AI applications for IoT enable the prediction and possibility to avoid unwanted business scenarios, increase operating efficiency, and innovate new products with better risk management. It directly works on solving the following challenges
Unplanned business scenarios
An undetected simple equipment deficiency can bring big downtimes for certain businesses. IoT and AIML work hand in hand to allow Predictive maintenance, predictive production according to sales, predict sales dropping, or any other unwanted scenario.
Fluctuating operational efficiency
AI-powered IoT can help to stabilize and maintain consistency in operational efficiency. It generates insights on operating conditions and suggests necessary adjustments.
Finding space for less risky innovation
What’s the point of producing if we can’t sell accordingly? With the powerful analysis, we can predict the suitable products and services that replies to customer expectation providing new opportunities for open innovation and reeling new products with optimized risk management.
Difficult risk control
Pairing IoT with AI helps increasing safety as organizations can better understand and predict a variety of risks as well as automate their operations for rapid efficient response, enabling them to better manage worker safety, financial loss, and cyber threats.
Applications of AI in IoT apps
Today, a large portion of business investments in artificial intelligence in an attempt to replicate human intelligence, as it includes independent learning and problem-solving merged with all benefits of the Internet of Things that connects, computing devices and machinery elimination human mistakes and human-to-human interaction or at times, even human-to-computer communication. To simplify it is where You don’t need to move much and let automation do its job. Doesn’t this make life much easier?
It is noticeably present in
- Facial recognition tools
- Spam filters that segregate emails
- Chatbots for customer service on eCommerce webpages
- Self-driving cars
- Google search engine technology
- Product recommendation engines on e-commerce websites
What we do at IndiaNIC
At IndiaNIC we are constantly reimagining the boundaries of artificial intelligence and machine learning to help global businesses efficiently utilize their assets and Unlock the new possibilities by meaningful integration of AI and ML technologies to IoT applications.
Here are some solutions we offer for different domains
Connected Autonomous Vehicles power computer vision that enables autonomous vehicles to “think”, interact with its owner and provide meaningful insights
Predictions on Patients’ Health AIML health predictions based apps
Precision Farming & Cultivation smart AIML and IoT sensors that detect detecting diseases and malnutrition
Magic Mirrors for Virtual Try-on the latest additions to the fashion online retail world allowing to try on makeup and clothes Smart mirrors/ camera combine sensors
Smart Homes with voice detectors
control your home by voice functioning and your personalized app
Recommendation Engine smart data analysts of user preferences enabling matching suggestions to his expectations
The world is still looking to see more apps booming from smart use and implementation of AIMl and IoT driven technologies providing comfort and the best user experience possible