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Artificial Intelligence and Machine Learning Services
Our Business Intelligence Solutions for IoT Applications

Artificial Intelligence (AI), in at least one of its various forms, has had an impact on all major industries in the world today. AI has been growing rapidly in the past few years, as there have been several advancements in data collection, analysis and processing.

The key contributors to these advancements are robust Internet of Things (IoT) connectivity and high-speed processors to fortify it.

At Embitel, we are constantly reimagining the boundaries of artificial intelligence and machine learning to help global businesses efficiently utilize their IoT assets.

Various Streams of Artificial Intelligence

Artificial intelligence, as is commonly prevalent today, is also referred to as Narrow AI (ANI). This stream of AI pertains to technology outperforming humans in a narrow spectrum of cognitive abilities. Some examples of narrow AI are:

  • 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 ecommerce websites

Today, a large portion of business investments in artificial intelligence are for narrow AI.

Another stream of AI, referred to as Artificial General Intelligence (AGI), enables a machine to apply skills pertaining to multiple streams of cognitive abilities. This is a replica of human intelligence, as it includes independent learning and problem solving.

Machine Learning (ML) and Deep Learning are Subsets of Artificial Intelligence

Machine learning involves the usage of complex algorithms that automatically learn and refine the learning from a vast amount of data and data patterns. The performance of these systems plateau after an extended period of training.

Deep learning, on the other hand, is a subset of machine learning. Large neural networks (complex algorithms with brain-like functions) are constructed and trained with a huge amount of data continuously. The performance of these networks improves as the training increases. This results in the development of machines that can predict outcomes through deductive reasoning and logic.

Our AI and ML Services for IoT Applications

We assist customers in identifying AI opportunities for improved efficiency of operations. Our decade long expertise in AI and ML software development can be leveraged to build intelligent systems that effectively automate tedious or repetitive tasks.

 

Data collected by IoT sensors can be in the form of text, videos or images. Data mining activities include the consolidation of raw data, cleansing, analysis and segmentation. Only the data in a suitable format is used for further processing.

 

Our team of ML experts support customers in developing self-learning algorithms that accurately process large sets of data and deliver insights. We perform feature engineering, model training and model validation activities to ensure maximum accuracy of predictions.

 

We assist you in developing AI-powered mobile, web and desktop applications that can monitor assets over time and predict possible failures before they even occur. Such predictive analytics systems are widely used in industrial and enterprise operations. We also help you develop ML-powered wearable devices that can track human movements or vital signs and derive valuable insights.

 

Our team of ML experts support customers in developing self-learning algorithms that accurately process large sets of data and deliver insights. We perform feature engineering, model training and model validation activities to ensure maximum accuracy of predictions.

 

End-to-End Engagement for AI/ML Solution Development

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IoT Sensors for Data Collection

Hardware and Software Development services for IoT Sensor Nodes
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Data Cleaning, Filtering and Feature Extraction

Identification of relevant data parameters from the set of raw data collected by the IoT Sensors
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Evaluation and Identification of the ML Model

Identification of a suitable Machine Learning Model (neural networks, decision trees, regression models, classification models, etc.) based on the problem-statement and parameters
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Training the ML Model

Segregation of filtered data into ‘training data’ and ‘validation data’
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Outcome Prediction, powered by ML

Training the model through exposure to a large amount of real-time and historical data so that it makes predictions with a high degree of accuracy
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Strategy Consulting

Design and development of cloud-based SCADA solutions, other web-based desktop applications, mobile apps, HMI/UI.

Artificial Intelligence Use Cases

AI based software solutions for mobility/autonomous cars:

Smart location tracking

Navigation

Control of cabin conditions

Automotive entertainment

Connectivity with mobile devices

Control of drive modes

Parking assistance

Intelligent mobile app

Driver behaviour monitoring

Assessment of road conditions

Other avenues:

Sports applications/wearables powered by machine learning

AI-enabled health monitoring devices/wearable

Predictive maintenance for battery monitoring and solar tracking systems in Industry 4.0

Why Choose Embitel?


1

Deep domain knowledge in artificial intelligence and machine learning to take up consultation and development projects.


2

Experience of over 10 years in crafting AI/ML solutions for global customers across industries.


3

Custom development of AI/ML solutions to mitigate business-specific challenges.


4

Speed, flexibility and transparency in delivering cutting-edge solutions.


5

Expertise in full-stack IoT development to integrate your AI/ML solution to an existing IoT infrastructure


6

Data safety and quality of deliverables are attributed top priority.


Customer Success Stories

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Handbook: IoT Solutions Powered by AI and ML

Partner with us for unlocking the potential of Machine Learning algorithms for your business challenges.
Our solutions drive business automation through improved and accurate decision-making.

The Key to Unlock Success Through AI and ML

The essential factors that guarantee success of an artificial intelligence implementation are as follows:

  • Collaborate with partner companies driving IoT innovation. The alliance should augment the goals of both companies.
  • Aim for a harmonious collaboration between human and machinery assets in your organization.
  • Ideate the incorporation of IoT across segments and in your overall business operations for improved productivity.

 

Meet Our AI/ML Leaders

 

 

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