GNSS IoT Positioning: From Conventional Sensors to a Cloud-Based Solution
Vicente Lucas-Sabola IEEC-CERES, UNIVERSITAT AUTÒNOMA DE BARCELONA
Gonzalo Seco-Granados IEEC-CERES, UNIVERSITAT AUTÒNOMA DE BARCELONA
José A. López-Salcedo IEEC-CERES, UNIVERSITAT AUTÒNOMA DE BARCELONA
José A. García-Molina European Space Agency, ESA/ESTEChttp://insidegnss.com/gnss-iot-positioning-from-conventional-sensors-to-a-cloud-based-solution/
The advent of the Internet of Things (IoT) has considerably increased the number of services and applications that require positioning information. In this sense, IoT positioning sensors usually obtain and deliver their position to a central node where it is further managed and analyzed by a user or scheduler. Nonetheless, the stringent requirements of low-cost IoT sensors in terms of low power consumption to achieve larger battery lifetime are pushing current technologies to their limits. In this context, we propose a cloud-based Global Navigation Satellite System (GNSS) solution to deal with the typical constraints faced by IoT sensors by migrating the signal processing tasks from the sensor to cloud servers. Theoretical and experimental results demonstrate the feasibility of a cloud-based GNSS approach in energy efficiency, performance, and economic terms.
This article discusses the conventional solutions for IoT positioning, with GNSS-based solutions being the most widespread in positioning IoT sensor networks. The architecture of a conventional GNSS IoT positioning sensor (Figure 1(a)) has been addressed, together with the energy consumption of its different components, showing that the GNSS module is the largest consumer if the data to be transferred is not large. To tackle the dilemma of energy consumption in IoT positioning sensors, we propose the use of a cloud-based GNSS approach, in which the purpose of sensors is just to capture the GNSS signal and send it to a cloud server where it will then be processed.
The energy consumption of the proposed cloud GNSS IoT sensor (Figure 1(b)) has also been addressed and compared with state-of-the-art GNSS IoT positioning sensors. Under the constraint of working with a relatively small signal length, the use of the cloud GNSS receiver achieves a significant savings in the sensor’s consumed energy, up to one order of magnitude compared with hot and assisted starts, and up to roughly 2.5 orders of magnitude in contrast with warm and cold starts.
Finally, the economic cost implied by the use of cloud services to process the GNSS data and obtain the position of the sensor has been shown to be low, thus ensuring the cloud GNSS receiver as a low-energy and low-cost solution for IoT positioning.