Minimizing Power Budgets to Enable Geolocation on Every IoT Device

Leveraging the cloud and minimizing time-to-first-fix opens the door to truly ubiquitous IoT positioning

The IoT roll-out continues apace with the number of IoT devices worldwide forecast to almost triple from 8.74 billion in 2020 to more than 25.4 billion by 2030. As a growing number of these devices are expected to be used for positioning and tracking, there is increasing demand for them to offer geolocation functionality. However, there are significant challenges of integrating accurate geolocation into an IoT node.

One of the problems of using conventional ‘consumer-oriented’ geolocation architectures in new and emerging IoT tracking applications, for example, is that they are power-hungry, not least when it comes to the GPS chip. And while typical power consumptions may be acceptable for a sports watch or a phone that is going to be charged regularly, they can destroy the value proposition in IoT solutions expected to operate over long periods of time without changing or charging a battery. In addition, the need for multiple chips and associated circuitry demands a form factor that may not be feasible for many IoT implementations, as well as dictating a price that is almost certainly too high for low-cost, high-volume deployment.

It is clear that to address the power, size and cost challenges of the latest IoT positioning and tracking use cases a new approach is needed. One such approach, as explained in Nestwave’s new whitepaper ‘Minimizing Power Budgets to Enable Geolocation on Every IoT Device’ is to implement a GPS receiver in software that makes use of the existing radio and computing capabilities of IoT chipsets and eliminates the need for an external GPS chip. And if such IP is combined with cloud-based processing that splits the processing pipeline to offload some of the more complex, energy-intensive computation to the cloud, then the IP power can be kept as low as possible by greatly reducing the time during which the IoT chipset is active.

Among the topics covered by the whitepaper are why conventional tracking architectures are not suitable for many IoT implementations and the importance of factors such as time-to-first-fix (TTFF), the number of fixes and levels of integration in determining power consumption. The paper introduces new ways of handling positioning signal acquisition, ranging and tracking and provides data that quantifies the potential benefits of using a hybrid IP and cloud-based approach.

To download a copy of the new whitepaper visit:

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