In LoLiPoP IoT innovative Long Life Power Platforms will be developed to enable retrofitting of wireless sensor network modules in IoT applications. This includes the development of algorithms to perform FUNCTIONALITIES for asset tracking and condition monitoring (for predictive maintenance). They are used in APPLICATIONS for industry 4.0, smart mobility and energy efficient buildings. LoLiPoP IoT creates an ecosystem of developers, integrators and users to develop these platforms focusing on lower power consumption/longer battery life, ease of installation and maintenance. The project is driven by 12 laboratory and field-based use cases demonstrating their technical viability and potential impact.

The use cases are Asset tracking (Med Tech factory, orthopaedics factory, aviation asset), Condition monitoring (spray painting tool, smart bearings for e-vehicles, hydraulic equipment, mobile device fill level) and District Heating and Healthy buildings.

Expected impacts from the LoLiPoP IoT use cases include;

a) typical battery life increase from ~18 months to >5 years,

b) Reduced maintenance overhead of mobile and fixed assets from >30% to <15%,

c) Reduced costs related to location of assets by ca. €100Ks PA per use case,

d) Optimised flow, management and throughput of assets through the identification of bottlenecks, yielding reductions of >10% in production time, cycle time and inventory costs,

e) Improved comfort levels and well-being of building occupants whilst reducing energy footprint by >20% and

f) Revenues of >€10M PA for LoLiPoP IoT industry partners offering asset tracking & condition monitoring services.

All of this is achieved by developing and integrating:

a) Multi-source Energy Harvesting solutions (vibrational and photovoltaic transducers, power management circuits and ICs),

b) Digital interfacing to contextually adapt mode settings of WSN devices and connected systems to minimise power drain,

c) Ultra low power components reducing WSN power consumption,

d) Innovative Architectures for wireless data collection that minimize battery power drain, e) Simulation Models to optimise component design and integration, and f) Embedded AI/ML in IoT devices for lower latency, higher robustness and reduced power consumption.

The challenges addressed by LoLiPoP IoT cover most of the concerns related to energy by using energy harvesting, micro power electronics & IoT design, machine learning algorithms for sustainable ECS solutions focusing on the vision of the EU Green Deal for a clean and circular economy. The main pillar for a future energy harvesting and micro power electronic industry is foreseen by the sustainability of electronics that imply a feedback technological flow, to 99% reuse of the output products transformed in waste, then back to input, as raw material. LoLiPoP IoT will support solutions for technology reutilization, for use of materials with lower impact on environment, employ methodologies (hardware and software) for lowering the energy consumption over the whole lifecycle of the project to facilitate the move towards a circular economy.