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The remainder of this paper examines two EG 3.0 scenarios supported by BC 3.0 and AI technology, the purpose of which is to provide EG stakeholders and policymakers avenues to exploit current industry BC and AI applications for governmental, public, and social good.
Energy data – Scenario1Scenario 1
In recent years, digital smart city governance with ICT expanded and regional research addressed the increased energy demand that emanated from the multiplication and complexity of Internet of Things (IoT) devices. It became crucial for local governments to practice energy management strategies and use available energy efficiently [32]. A modern smart city applies smart technologies to its infrastructures and to citizen residences. The EG 3.0 scenario includes IoT devices, installed at citizen residences, that produce energy; these citizens are referred to as prosumers. This ability of energy consumers to produce energy from renewable sources and distribute that energy, through smart grids as prosumers, increases the difficulty of national energy management. However, prosumers also create the opportunity for smart city energy sustainability and efficiency when citizen produced energy is successfully modeled and incorporated into city energy systems along with energy related to transportation and facilities [33]. Energy management is critical; the European Commission, in the last two years, published two directives for energy efficiency goals with a 20% energy savings target by 2020 and a 30% energy efficiency target for 2030. Additional, specific national targets include lowering energy bills, reducing nation’ reliance on external suppliers, and eco-friendly protecting the environment [42][43]. EG 3.0 supports citizen-sourcing, increases efficiency in all phases of the energy supply, and leads energy sector management. BC 3.0 technology, in conjunction with AI, provides authentication, decentralized intelligence, security, and collective decision making.
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A SC collects energy consumption and production measurements from prosumer IoT devices and logs them on the blockchain. The prosumer provides the BC login identity issued to her. This self-sovereign identity (SSI) ensures secure entry and prosumer user control [44]. A SC dispatches surplus energy from a prosumer residence to the main energy system or to a citizen-sourced smart grid. If, for example, daily consumption need is 14kWh and the SC detects the power produced from renewable sources exceeds 15kWh, an action automatically triggers and dispatches this surplus power to a pre-identified local energy system. A dynamic smart contract deposits the required, predefined payment for the energy dispatched to the prosumer’s account. Oracle-based SCs inform citizens how their energy dispatching can be more profitable and provide incentives for participants on the energy network. Smart grids, informed by local policies, consider geographic factors, energy needs, and building production capabilities. AI agents operate at citizen residences as collective decision-making mechanisms that apply Swarm Intelligence (SI) and achieve swarm goals [34]. SI calculates how much energy can be dispatched to a city’s central energy system and how much energy is available to be traded among smart grid participants. AI EG applications read data written on the BC and forecast city energy needs for hours, days, or months. AI analyzes data for trends or peak hours. The results and metadata from AI analyses are grouped per district to help governments and policymakers create more efficient energy management strategies as they achieve local and national goals.
Health data - Scenario 2
National Healthcare systems are another a sector where e-health strategies must be adopted for governments to control excessive healthcare costs [35]. Healthcare systems hold massive amounts of confidential data; problems arising in processing and analyzing this big data are solvable with AI. Research shows older adults struggle to use e-health systems [36] [37]. With AI chatbots speech recognition support older adult questions and inquiries; chatbots can provide responses and guidance. AI agents also support patient forms completion and submittance submittal to appropriate government departments [38]. A permissioned BC 3.0 secures confidentiality and authenticity of private e-health data. EG 3.0 provides solutions to e-health priorities by utilizing ICT and Web 3.0 to transform legacy systems, increase their efficiency and effectiveness, decrease costs, and provide citizen-centric health care services [36].
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