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We develop and promote technologies for regional needs by partnering with leading academic research establishments and global technology labs of Hitachi. These associations enable us to strengthen solutions for our different business areas, such as finance, public safety, healthcare, automotive, and urban development.
To deepen customer co-creation and contribute to social innovation business, our researchers in India work in close collaboration with our Japanese counterparts, and utilize their technologies for rapid co-creation with Indian customers.
Hitachi’s Payment service research activity focuses on developing data analytics solutions, targeting operational improvement of ATMs, Point-of-Sale (PoS) and other emerging payment channels. For instance, we research on solutions to enhance the efficiency of merchant management services by analyzing merchant’s behavior, while identifying suspicious payment transactions. We provide solutions to forecast demand for cash replenishment of ATMs so that alternative routes can be planned with the objective of reducing instances of out-of-cash situation or idle-cash situation at ATM sites.
Healthcare and pharmaceutical sectors are embracing data analytics for value-based healthcare and improvement in drug-discovery processes. However, the unstructured data available in these sectors poses big challenge for data scientists and AI applications to consume the data.
Our R&D team strives to address these data analytics challenges through a combination of rule-based and machine learning methods for precise extraction of target entities using natural language processing technology. Some of the key capabilities developed by us are to extract disease or disorder names, numerical attributes, temporal information, clinical trial sample sizes and efficacy information. We also participate in global competitions to constantly benchmark ourselves with peers. For example, our research team participated in CLEF 2014 where we achieved 1st place with an extraction precision of 86.8% in CLEF e-Health 2014 Task2.
Our Video analytics research focuses on development of image recognition algorithms to solve various use cases in the areas of Advanced Driver Assistance System (ADAS), environment monitoring, public safety, etc. We are developing both conventional image processing and deep learning techniques for detection and classification of various objects such as vehicles, auto-rickshaws, pedestrians, traffic signs, speed-bumps, etc. We also develop model compression techniques to deploy these algorithms into low memory processing environments, such as embedded systems.
Monitoring and control of social infrastructure equipment for highly efficient operations has become a major requirement for Internet of Things (IoT) systems. Hitachi has developed Rotating Polarization Wave (RPW) technology that realizes highly reliable and secure data communication with lower maintenance costs. RPW is a new transmission mode of electromagnetic waves in which the polarization angle is rotated at an optimum rate to minimize the distortion caused by surrounding infrastructure; thereby providing reliable communication under harsh radio propagation scenarios. We undertake collaborative research for experimental verification of such new technologies with the leading academic institutes in India.
IoT-enabled analytics plays a critical role in urban administration to make public transportation more accessible, convenient, and reliable for passengers. Hitachi has developed technologies to accurately measure urban road congestion through GPS data, and passenger crowdedness based on video analytics and ticket data analytics.
At Hitachi, we conduct research to optimize public transportation operations to realize secure and comfortable urban mobility. To efficiently analyze and visualize the big-data generated by these processes, our researchers focus on development of common analytics framework for easy reuse of solutions across industry verticals in global partnership with other Hitachi overseas labs.