Nowadays, it's hard to imagine life without smartphones. These devices surround us and have become an inseparable part of our daily lives, since they provide end-users with unlimited access to information, services, and communication through their multitude of sensors and computational capabilities. Through sensor-rich smartphones, it is possible to collect pervasive crowdsourced signatures. Manual training approaches to localize these signatures and construct offline radio and magnetic maps required for fingerprinting-based positioning techniques are time-consuming, labour-exhausted, and restrict the scalability of ubiquitous signals, such as Wi-Fi and magnetic field. As an alternative, autonomous localization of pervasive signatures can eliminate human supervision and scalability barriers, prompting to development of self-deployable systems. The development of these systems offers unparalleled potential for extending the ubiquity of indoor positioning systems (IPS) and makes realizing ubiquitous IPSs one step closer. This study proposes a scheme to leverage pervasive crowdsourced data to develop a ubiquitous IPS without the need for external resources.