The project OPEVA aims for innovation on aggregating information from the vehicle, not only from the battery but also from other internal sensors and behaviours, to create a model of performance and consumption specific to the individual vehicle and its driver (TD1). It aims to optimize the individual driving episode using the out-vehicle data such as state of the road, weather, charging station location and occupancy etc. that are collated from the back-end systems (TD2). OPEVA will further address the challenges associated with the communication between the vehicle and the infrastructure to gather data from the back-end systems (TD3). It aims for innovation in the use of recharging stations and related applications (TD4). It further aims to achieve better understanding on what the battery and its constituent cells are really doing during real world use for an improved battery management system (TD5). Finally, TD6 covers the driver-oriented human factors for optimizing the electrical vehicle usage. The TDs from the most deeply embedded in the vehicle to its support in the cloud, which need to interwork in an optimal fashion to deliver in one decade a better level of systemic optimisation for personal mobility that took ten decades to achieve with fossil fuels. On the other hand, economic factors (N-TD1), legal and ethical aspects (N-TD2), EV related development by the human (N-TD3), and societal and environmental factors (N-TD4) will be taken into consideration in the OPEVA methods for a higher acceptance and the awareness of the society regarding the these developments.

Humankind has progressed quite a lot with building machines that it can talk to, and that respond with something resembling natural speech. The society is in a transition point where voice and natural-language understanding are suddenly at the forefront.At the same time, mobile usage is growing worldwide and so mobile shopping. Conversational commerce , a.k.a. conversional shopping, is a trend emerged from the use voice search via mobile personal assistants. It transforms all interactions with a brand or merchant into a natural conversation – from shopping assistance to customer support. The introduction of voice search was just the beginning. In fact, companies are starting to have a more conversational approach online using messaging, digital assistants, chat apps and automated, machine learning dialogue to engage with the consumer, offering them the opportunity to interact with brands and services (chatbots and vocal assistants). In fact, speech recognition market is expected to grow from $ 3.73 Billion in 2015 to reach $ 9.97 Billion by 2022 (at a CAGR of 15.78% during the period), whereas voice recognition market growth is expected from $ 440.3 Million in 2015 to $ 1.99 Billion by 2022 (CAGR of 23.66% between 2016 and 2022). PERTIMM has detected a growing demand from Internet users and buyers for cost-effective, neutral and privacy-friendly services and from chatbot developers for platforms that support fast and cost effective chatbots development. VOQAL.AI main objective is to accelerate the use of the first European multilingual vocal assistant, collaborative, open-source platform for e-commerce, as first segment market, that guarantees Human Machine Communication (HMC), whereas granting independency of GAFAs (Google, Apple, Facebook and Amazon) data treatment and privacy. VOQAL.AI users will reduce between 80-90% of the cost and time in the chatbot development with an improvement by 200% the commercial conversion rate of ecommerce organizations.