Processed meat products have growingly become a popular solution for highly nutritive yet affordable meat for consume, having the global market for these products registered a remarkable increase in the past years. Once the prime cuts and main pieces of meats have been cut from the carcasses, there is still a substantial amount of muscle tissue attached the bones. The optimal use of this meat would be in processed meat products. In case the residual meat is recovered by hand, the product is considered as meat and legally treated as such. However, if the recovery is done mechanically, the product should be regarded as mechanically separated meat (MSM), a supposedly lower quality product, and treated as such in accordance to present EU legislation. Nowadays, mechanical methods are the industry’s preferred approach. Significant technical improvements in the mechanical separation processes have been seen during last years, which enable the production of MSM that cannot or can only hardly be distinguished from manually-processed minced meat. Thus, there is a need to establish an objective and accurate method to quantify the degree of degradation of muscle structure, as there are no objective arguments supporting the separation of MSM and minced meat. Building from this, we have developed a highly reproducible histochemical method for the harmonization of the assessment of meat quality in laboratory quality control settings as well as fast and objective method to perform online quality classification of comminuted meat at the production line. Through the present innovation project, we will demonstrate the economic benefits to end-users and added value of our technology for meat industry market. Moreover, the accomplishment of the project objectives will represent a major business opportunity, with an estimated 5-year aggregated turnover of almost €23 million.

Recent developments in the Electric Vehicles (EV) technologies have made great strides to offer new modes of smart green urban mobility, where EVs are used as the main transportation mode replacing the conventional diesel and petrol powered vehicles. EVs are expected to play a key role in achieving ambitious targets of lowering greenhouse emission in the transportation sector. Given the EV penetration rates and future forecasts, it is essential to develop technologies that tackle charging management of EVs considering a holistic view of charging supply/delivery management for EVs, communication of EVs to the smart grid infrastructure system using 5G and beyond systems, smart grids and big data analytics for EVs optimise smart mobility and enhance the quality of experience for EV users. EVOLVE aims to exploit the scientific excellence and expertise of key academic and industrial players into a joint collaborative effort to design, develop and test various technologies that consider the holistic view of EV charging taking into account the view of technical and business stakeholders. EVOLVE will pursue innovation for advancing the technologies in EV charging ecosystem by orchestrating and managing the underlying networking and computational resources, design innovative algorithms using Artificial Intelligence (AI) and Machine Learning ML), developing communication protocols, prediction and optimising load in smart grids, developing software systems and user interfaces (UIs). EVOLVE aims to transcend analytical models and simulation-based validation and aims to deliver five proof-of-concept (PoC) demonstrations. EVOLVE project will provide a platform to foster a close collaboration between academia and industry partners providing each with a unique experience to create new knowledge, share know-how and skills development.