{'fraction_non_alphanumeric': 0.011965811965811967, 'fraction_numerical': 0.0, 'mean_word_length': 4.9727891156462585, '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}}
A feasibility study of the remote data acquisition system on vehicles

As vehicle systems become more complicated, it takes longer to analyze the malfunctions. Collecting the useful data can shorten the time to analyze such malfunctions in vehicle systems which consist of many sub-systems. The conventional remote data acquisition systems can only collect the fixed set of data, and the dedicated measurement instruments are required to collect the data under various conditions. We proposed a new system which can collect data under various conditions by effectively utilizing the existing resource of the car navigation head unit. The system is designed to be a useful tool for the engineers to collect data to identify the unknown cause of the vehicle malfunctions. Our proposed system connects the center and the vehicle via the wireless network. The center sends the condition of data acquisition to the vehicle. The condition is described by the script language. The navigation head unit has an interpreter program to interpret conditions, and is equipped with several APIs to allow the data acquisition system to use some of the Navigation functions including location. The engineers can describe the various conditions to get variety of data from the vehicle by the language operator, control statement, and various APIs. We chose the interpreter program which is commonly used in embedded devices. The system is capable of collecting various data from the vehicle without adding any resource to the existing navigation head unit. We conducted the actual vehicle experiments to verify the basic performance of the system. Our proposed system is able to collect all CAN data frames under the test condition using the six different types of CAN-ID.