From our perspective as industry professionals, we need to look at indoor positioning as not a single market, but instead as a multitude of emerging markets. As a business, we need to find a model that can finance that belief. Over the past decade we have all looked into ideas, solutions, different techniques, however… who really understands the value chain?

Defining the business models

If we answer yes to the question of “Is there really a need for indoor positioning?”,  the question becomes : which business model and timing will sustain growth? Clearly, there is NOT just one business model, because the value chain and user requirements are so vast, the product lifetime is variable, and the market is still at an infancy stage.

Being robust, as compared to infrastructure-based solutions has a price

The cost of ours (and yours!) solutions range from engineering innovative ideas, whether that be hardware, software, in-house or out of the box marketing driven solutions. Being the best technology, does not, once again, define what the user needs. And at what price?

The technology in GNSS user equipment today is more diversified than ever before; ranging from miniaturised, low power GPS chips found in IoT trackers to much larger, more powerful and expensive receivers fitted in passenger aircraft. Furthermore, new models are being introduced at an unprecedented rate, driven by the growing performance requirements of innovative applications, developments in the semiconductor industry and to take advantage of the enhanced capabilities offered by new and modernised GNSS systems and services. In this rapidly evolving landscape, three primary dimensions of change can be identified for user positioning technology: ubiquity (continuous access to the location information everywhere), automation and ambient intelligence (e.g. enabling autonomous vehicles that can sense their environment and adapt to it) and the provision of more robust, secure solutions (resistant to interference and respecting the privacy of the users). The GNSS user technology is, now more than ever, experiencing a rapid and exciting evolution. During the presentation I will summarize the main findings of technology research in this area performed by the GSA and answer to the question “what works best in geolocation?”.

Microtechnology comes of age. Clearly, some significant advances have been made, and we see a footprint of the inertial sensors technology in an ever-growing consumer electronics market full of interactive products enabled by microtechnology. These products include, for example, accelerometers for gaming, gyros for auto safety, resonators for clocks, and more. The questions remain, however: Is the technology really on the level of what we consider to be precision sensing? Is making sensors small necessarily result in degradation of performance? Why do we need the precision of sensing for our daily life and what are the opportunities if we have the precision at our fingertips? I will talk about some of the recent developments toward precision sensing, including an overview of glassblowing technology for 3D wineglass shell gyroscopes, silicon origami-like 3D assembly techniques for solid-state and atomic MEMS, and the futuristic concept of the Ultimate Navigation Chip (uNavChip).

Humans inherently possess a good quality ”stereo camera”, namely eyes, which is their most important navigation tool. Vision is especially important for choosing the course. Early studies have shown that people tend to veer when blindfolded, which leads them walking in circles and getting lost. Therefore, the use of visual landmarks is the most accurate means of human navigation. It is not a surprise that computer vision is an essential part of navigation of autonomous vehicles. Human visual perception is capable of filling in missing information enabling the understanding of perspectives and evaluating distances and occluded parts of the objects in the scene, but for computer vision objects in the scene are just sets of points of digitized brightness value functions. Although sophisticated methods already exist, extensive research is still needed for obtaining reliable navigation solutions using computer vision. During this presentation, the use of different means of computer vision in navigation are discussed with an emphasis on the most challenging use case, infrastructure-free pedestrian navigation.