Machine Learning Applications in Sports, Fitness and Health

How Machine Learning and Artificial Intelligence are applied in sports to improve player’s performance?

Technology has entered every sphere of our lives, Artificial Intelligence (AI), Machine Learning (ML) and Data Analytics are changing the paradigm. Technology is everywhere, how sports can remain unscathed?

Our “Sensei” Sports Wearable Platform with Edge AI

Artificial Intelligence in sports is an emerging field, though, the trends suggest AI is the next big thing in sports with its promising features; sport is going to witness radical changes in coming years. Because AI aided performance management and training enables a prompt and automated evaluation of sport-specific parameter values. As AI scales better on large scale with quantitative metrics than the human capability.

What is Artificial Intelligence?

AI is the intelligence created with the use of machine and lots of data. A machine is programmed to imitate human cognitive abilities such as learning and problem-solving using data and algorithms. Consequently, the machine starts learning from its own experience with the help of these algorithms and data provided.

How Machine Learning is applied in Sports?

With the advent of AI in sports, the machine and analytics are being used to provide a feedback mechanism for player’s performance and to set goals. Technological devices are being built to improve sport performances. One of the most featured devices is the wearable wrist band, specifically designed for sports loving individuals, they provide a promising and comfortable platform for sports analytics.

With AI power, these wearable devices have in-built sensors to record the movements of a player and monitor the natural phenomena. These wrist bands are capable of tracking and analysing microscopic variations to maximise the player’s proficiency. With the sensor readings of heart rate and continuous movement information, they show variations in the case of any discrepancy.

This device provides a ‘quantified self’ statistics derived from performance measurements. The cumulated stats allow the software to learn from incoming readings and identify factors that affect the measurements, and get better with more and more data over time. By combining these data with powerful smartphone and web apps, players can be provided with real time actionable insights and guidance.

Like in any sport, a coach provides a guidance by watching strokes, spotting errors, and inefficiencies in the player’s form. However, the judgement and targets usually come from the coaches as per their personal evaluation and have human limitations.

For example, in Tennis, these bands provide information on the speed, spin, and placement of a tennis serves, enabling a mechanism to capture valuable metrics that were previously difficult to gather or obtained manually. But now previously undetectable metrics are available in an instant. These statistics, then could lead to draft a better vision for trainings.

How a wearable device functions?

A wrist-worn device easily read different movement patterns for a forehand shot, compared with a backhand; it detects similar movement patterns and group similar data together. It creates movement classifications for events like serves, and shots such as forehand, backhand, and volleys providing a statistical analysis-based feedback. This helps to develop real-time game strategies and improve playing techniques, making right decisions and create alerts in the case of a potential decline in the performance. This device can easily help the coach to get multiple players better at their games simultaneously.

It is every sport person’s dream, a technological aid for performance improvement and guidance.   

Wouldn’t you be delighted to track your record on every stroke, identify your areas of improvement, detect opponent’s strengths and weakness with the factual accuracy?

OptimusLogic’s ML Solution for Sports, Health & Fitness:

We, Optimuslogic Systems, are working to bring this value in the field of sports, fitness and health to users in India, with an ongoing design to create world class devices with remarkable application of Sensors, Product Design, Artificial Intelligence (AI), Machine Learning (ML) and Data Analytics. 

We internally call our wearable, “The Sensei” – or the Teacher.
“The Sensei” is currently learning sports actions by itself using ML, and it is indeed proving to be a fast learner, thanks to SensiMLTM Toolkit – the breakthrough edge AI development tool for the smallest of  IoT devices, which runs on our custom ultra-low power sensor device platform.

Once the Sensei masters its game to reach 90%+ accuracy, it will teach end users how to play well and be healthy! The Sensei can learn human actions in a matter of days and be able to classify the movements without connecting to the Internet or cloud. And yes, we can pair the Sensei with any of your cloud, apps or systems to get a connected game play or fitness experience.

If you are looking for a similar ML powered system to integrate into your product, that can learn and understand human and machine movements quickly, please contact us at

Watch this space for more updates on “The Sensei” …

Water Meter Reading with Cameras and ML: An Economical, Reliable, Maintenance-free solution today!

2019 has been the year of Water! Acute Water Shortage in Summer across India and now devastating flood in the Rainy Season. Our prayers with all those affected!

With rising apartments and rising cost of water, there is sudden demand for individual water metering across homes, offices. I have seen a number of start-ups jumping into the fray with “Smart” Water Meters. Its good to see the indigenous push towards water meters, with ultrasonic measurement, telemetry, accuracy etc.

While it is tempting to get the “state of the art smart” meter, it is very important to first weigh your true needs of metering with the long-term costs of continued maintenance, repair, service contracts and subscriptions over next 5-10 years, especially with the poor water quality with “hard water” and scaling – All considering that the water supply in India comprises of mix of public utilities, borewells and tankers, resulting in poor quality of water flowing through pipes.

Example of Common Mechanical Dry-Dial Water Meters in India – Economical, Reliable, Maintenance-Free

Considering maintenance-free operation across all types of water, its natural to turn towards the good old Mechanical Meters that have been doing business in India for many years. These meters are economical (7-10$), ISI certified, easily available and above all, can deal with any water flowing through it for many years and needs no batteries to operate. We should continue to use such a reliable, mature technology for measuring water consumption.

The problem of getting the reading of mechanical meters to the cloud, or telemetry, can easily be solved by deploying latest low cost cameras on top of the meters at a fixed focus. The prices of camera modules have dropped significantly in the last year and we can pick up a 2MP Camera module operated by a Microprocessor at 5$-10$ retail price today without volume discounts.

Check out the ESP-EYE module based on the Espressif ESP32, which packs the 2MP Camera Sensor along with heavy duty Dual-core Microprocessor with WiFi/BT/BLE in a small form factor.

If we put such a low cost camera to infer the reading from a mechanical water meter, the benefits of such a simple to deploy system would be fabulous.

A basic Machine Learning system would easily be able to recognise the meter reading from the image of the water-meter on the Edge using Tensor Flow or similar tools – given that the image and the meter is always in the same lighting, same position and same model across all units. This approach can be scaled to a large number of apartment units using industry grade RS-485 and M-bus protocols to create a maintenance free, reliable and economical solution. Wise Water Meters seeks to use our method for the solution, check out their website for more details.

Here’s what we did so far; We put such a camera-module on-to a Mechanical Meter to capture the images and generate a ML model on the server. While the ML model is being developed, there is a manual backend to catalogue these images and arrive at the right reading today itself – This allows us an automated real-life scenario to get real meter images for ML learning while ensuring customer is happy from Day 1. Once the ML model will be stable, all manual classification will be avoided and the whole system will be autonomous.

I expect the final ML Model on the Edge to be ready in 2 months along with our production ready design of the telemetry unit that fits as an after-market on popular mechanical water meters in India. Checkout one of our prototype deployments at home… Reach out to us at, if you want to partner in commercialisation or have better ideas about this.