Decentralized resource management is a promising field as it has the ability to lessen impact on Earth′s climate change, assist with renewable technology development, increase equity in the distribution and consumption of resources, decrease vulnerability and enable participation of local people and businesses in the supply of technologies. Alternative energy and water resources are widely researched to provide self-sufficiency in scales of single houses to communities, but are still limited to demographical, technological, economical and social factors, which vary around the globe. Infra-Free (IF) is an academic research that seeks a synergy between relevant research fields to promote different decentralization scenarios for combined energy and water technologies with best-performance. The Infra-Free Motherboard (IFM) is a proposal for a standardized platform, where installed technologies integrate within a household as robotic systems that evolve into a self-aware artificial platform to provide customized resource management. It addresses a multidirectional, real-time processing artificial resource management system that could develop its own skills by close interaction with the environment and the user. The system is enhanced with algorithms and dynamic systems to provide communication between different co-evolving systems that plug-in, adapt, evaluate and finally, customize themselves to dynamically changing environments due to resource availability, local needs, technology readiness and individual choices. The multidirectional real-time processing system further extends into a community application, where intelligent self-learning systems are aware of the amount and availability of resources in the whole network (community) and control the distribution between subsystems (houses) using best performance principles. Finally, this provides a dynamically transforming community that learns, adapts and redesigns itself. In this paper; at first, we introduce the standardized IFM and modular sub-system architecture. Next, we describe the hardware (platform) and software (self-learning process) architecture for the purpose to realize a customized real-time energy management system in a community of interconnected houses with a special focus on energy equation strategies. Next, we study a scenario to apply IFM in a small-scale community (100 people) in Masdar in 2012; integrated with a plug-in car concept, CO2recycle, evaporative cooling and Stirling engine system. Finally, we analyze the energy equalization potential of IFM in a computer simulation for a 6-household cluster (25 people).