{'fraction_non_alphanumeric': 0.029171528588098017, 'fraction_numerical': 0.0011668611435239206, 'mean_word_length': 5.172661870503597, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Exploring Approaches to the Management of Physical, Virtual, and Social Sensors

As the Internet of Things (IoT) get bigger and more complex, efficient and effective management solutions must be developed and put into operation. IoT management is even more crucial if we want to have a unified management that can cope with electronic, virtual (software) and human-based sensors, which provide contextualised data via Online Social Networks (OSN). In this paper we present and explore approaches to this unified management, resorting to open and widely adopted standards for both data and device management, namely OMA - Lightweight Machine to Machine (LwM2M) and FIWARE. We present a proof-of-concept (PoC) implementation that shows that the management of the referred three types of sensing is feasible from both functional and performance points of view.