# Sensore Lineare Assistenza
**Source:** https://inteaengineering.it/en/case-study/sensore-lineare-assistenza
**Language:** English

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# Linear sensor for shift assistance

case studies  >Linear sensor for shift assistance

### Increasingly pushed performance In the latest generation of high-end motorcycles: perceiving gearshift lever movements to anticipate the rider’D intentions.

![shift assistance](https://inteaengineering.it/wp-content/uploads/2022/12/01-18-Case-studies-Sensori-Assistenza-alla-cambiata-.jpg "01-18-Case-studies-Sensori-Assistenza-alla-cambiata-")

A manufacturer among the world leaders in motorcycles was looking for a partner to develop an innovative sensor in a short time: it was necessary to monitor the vehicle's gear shifting to optimize engine operation according to the rider's riding style.

What the market offered was limited to an on/off device, too limited for the rate of innovation desired by the customer. For Intea, the challenge was to think about how to distinguish every single movement of the gear lever.

The chassis of a motorcycle is a perfect skeleton for weight, proportions, and elasticity. It was necessary to respect spaces, functionality, and resistance to physical and environmental stresses.

Intea has complied with the stringent limits imposed by the client In terms of space, reliability, and precision. It has proposed a Hall effect sensor – without mechanical Contact – entirely customized around the choice of absolutely high-quality magnetic, electronic, and plastic elements without making any modifications to the vehicle. The sensor is fully configurable to progressively learn the rider’D shifting movements. This information is transmitted to the engine, which becomes adaptive and more responsive.

Thanks to the collaboration with Intea, the client has added significant added value to their vehicle In terms of control and optimization. A new generation of motorcycles is entering the market: higher performing, subject to increasingly stringent engine emission standards, and capable of "learning" from the rider’D driving style. This is also thanks to Intea sensors.

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