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Artificial intelligence based smart building Updated.pptx
- 1. Course Professor: Dr. Christopher Preece Group C
- 2. Introductio n Project Identificati on Project life cycle Work break down structure Project schedule Resources allocation Cost analysis Risk identificati on Mitigation of risk Conclusion
- 3. AI-based technology for energy optimization Reducing energy consumption in buildings Improving sustainability and environmental impact Lowering carbon emissions through AI Revolutionizing building energy management Enhancing operational effectiveness through AI Long-term energy sustainability goals achieved
- 4. P r o j e c t I d e n t i f i c a t i o n Description 01 Installing AI-based energy optimization system Streamlining energy use in intelligent buildings Monitoring and managing lighting, HVAC, and energy systems Cutting waste through improved efficiency Enhancing energy utilization in smart buildings Relevance of strategies 02 Relevance to climate change and emissions reduction Advancing sustainability and climate goals Lowering costs for building owners and occupants Increasing profitability and competitiveness Meeting the demand for energy-efficient structures Attracting investors and tenants focused on sustainability Problem Statement 03 Inefficient energy use in buildings Wasteful consumption and elevated expenses Lack of flexibility in traditional systems Dynamic optimization of energy use Addressing energy waste and utility costs AI-based system analyzing real-time data Forecasting energy demands for optimization Economic and Social Justification 04 Significant reduction in electricity costs Increased value and appeal of buildings Improved indoor spaces for occupants Boost in occupant well-being and productivity Lowering carbon emissions and promoting resilience
- 5. Project Life cycle Initiation Planning Execution Termination • Define project's goal, scope • To determine the technical and economic viability of applying AI-based energy optimization, conduct a feasibility study. • Determine the project's major stakeholders and their needs. • Create a thorough project strategy, taking into account data collection techniques, AI algorithms, • For the AI-based energy optimization system, specify performance measures and energy efficiency objectives. • Make explicit plans for procurement, risk management, and communication around AI technology. • Install the required hardware, such as sensors and meters • Set up the AI system to analyze data, forecast energy needs. • Work together with building technicians and operators to make sure the AI-based system is properly integrated and operating. • Describe the project's successes, difficulties, and suggestions for future implementations in the form of lessons learned. • Prepare project documentation and final reports, as well as revised manuals and instructions for the AI- based energy optimizations system. • To ensure the system's long-term sustainability and upkeep, conduct a post-implementation study. 1 Life Cycle Phases
- 7. Task Name Duration Start Finish Predecessors Resource Names Project initiation 36 days Tue 7/18/23 Tue 9/5/23 Project kickoff meeting 1 day Tue 7/18/23 Tue 7/18/23 Project Manager Stakeholder identification 2 days Wed 7/19/23 Thu 7/20/23 2 Project Manager Project communication plan 2 days Wed 7/19/23 Thu 7/20/23 2 Finance handler, Project Manager Need analysis 2 days Fri 7/21/23 Mon 7/24/23 4 AI expert ,Finance handler, Project Manager Requirement specification 4 days Fri 7/21/23 Wed 7/26/23 4 Data analysis engineer Project execution plan development 5 days Tue 7/25/23 Mon 7/31/23 5 AI expert ,Project Manager Project monitoring and control development 6 days Thu 7/27/23 Thu 8/3/23 6 Building operational Project cost analysis 3 days Tue 8/1/23 Thu 8/3/23 7 Finance handler project time line 2 days Fri 8/4/23 Mon 8/7/23 8 Project Manager Project total budget 5 days Fri 8/4/23 Thu 8/10/23 9 Finance handler Financial plan 6 days Tue 8/8/23 Tue 8/15/23 10 Project Manager Risk assessment and management plan 2 days Fri 8/11/23 Mon 8/14/23 11 Project Manager Project budgeting 3 days Wed 8/16/23 Fri 8/18/23 12 Finance handler Project evaluation and closure plan development 4 days Tue 8/15/23 Fri 8/18/23 13 Project Manager Stakeholder interview and surveys 5 days Mon 8/21/23 Fri 8/25/23 14 Finance handler Stakeholder identification 6 days Mon 8/21/23 Mon 8/28/23 15 Finance handler Stakeholder engagement plan 7 days Mon 8/28/23 Tue 9/5/23 16 Project Manager Project planning 93 days Mon 8/28/23 Wed 1/3/24 1 AL algorithm selection and its customization 10 days Mon 8/28/23 Fri 9/8/23 16 AI expert Research and Evaluation of AI Algorithms and Models 1 day Tue 8/29/23 Tue 8/29/23 17 AI expert ,Data analysis engineer AI software development or data acquisition 12 days Mon 9/11/23 Tue 9/26/23 20 AI expert ,Data analysis engineer Integration with Okland data center 15 days Thu 9/28/23 Wed 10/18/23 22 Building operational, Data analysis engineer Testing and validation of AI technology 20 days Thu 10/19/23 Wed 11/15/23 23 Building operational, Data analysis engineer Hardware deployment and sensor installation 20 days Thu 11/16/23 Wed 12/13/23 24 Building operational Connectivity setup for collection of data set 15 days Thu 12/14/23 Wed 1/3/24 25 AI expert ,Data analysis engineer Project execution 120 days Tue 11/7/23 Mon 4/22/24 26 AI system architecture 20 days Tue 11/7/23 Mon 12/4/23 25 AI expert Development of data analysis and decision making 30 days Thu 1/4/24 Wed 2/14/24 26 Data analysis engineer Configuration and calibration of system 4 days Tue 12/5/23 Fri 12/8/23 28 Data analysis engineer Integration along real time data collection 3 days Thu 2/15/24 Mon 2/19/24 29 Data analysis engineer sensor placement and development 5 days Tue 2/20/24 Mon 2/26/24 31 Building operational Sensor installation and configuration 6 days Tue 2/27/24 Tue 3/5/24 32 Building operational Continuous improvement and optimization 9 days Wed 3/6/24 Mon 3/18/24 33 AI expert ,Data analysis engineer Real time data monitoring and analysis 2 days Mon 12/11/23 Tue 12/12/23 30 Data analysis engineer Testing and debugging 10 days Tue 3/19/24 Mon 4/1/24 34 Building operational, Data analysis engineer Systems adjustment and optimization 10 days Tue 2/20/24 Mon 3/4/24 31 AI expert ,Data analysis engineer Data analysis and reporting 5 days Tue 4/2/24 Mon 4/8/24 36 Data analysis engineer Clearance finance 5 days Mon 1/8/24 Fri 1/12/24 54 Finance handler End 1 day Mon 1/15/24 Mon 1/15/24 59 Project Manager
- 8. Resource Name Type Initials Max. Units Std. Rate Ovt. Rate Cost/Use Accrue At Base Calendar Project Manager Work P 100% $20.00/hr $5.00/hr $200.00Prorated Standard AI expert Work A 100% $30.00/hr $10.00/hr $400.00Prorated Standard Data analysis engineer Work D 100% $20.00/hr $10.00/hr $500.00Prorated Standard Building operational Work B 100% $10.00/hr $5.00/hr $200.00Prorated Standard Finance handler Work F 100% $10.00/hr $5.00/hr $100.00Prorated Standard
- 9. Cost Analysis $0.00 $5,000.00 $10,000.00 $15,000.00 $20,000.00 $25,000.00 $30,000.00 $35,000.00 Project Manager AI expert Data analysis engineer Building operationer Finanace handler Actual Cost Remaining Cost Baseline Cost Name Cost Project initiation $14,360.00 Project planning $28,300.00 Project execution $31,320.00 Project Termination $15,080.00
- 10. Risk Identification Risk level 0 Risk level 1 Risk level 2 All sources of project task Technical risk 1- Scope definition 2- Requirement definition 3- Estimation and assumption along constraints 4- Al technology and algorithm Management risk 1- Project management 2- Scheduling 3- Stakeholder engagement 4- Resources 5- Communication 6- Risk allocation Commercial risk 1- Contractual terms and conditions 2- Internal procurement 3- Supplier and vendors 4- Subcontracts External risk 1- Client and customer stability 2- Partnerships and joint ventures 3- Legislation 4- Exchange rates
- 11. Establish open lines of communication to quickly address and address risks. Utilized appropriate risk management techniques, such as risk avoidance, risk transfer, risk mitigation, or risk acceptance. Utilized a reliable estimation procedure while taking pertinent assumptions and restrictions into account. Implement extensive testing and validation procedures to guarantee the AI system's accuracy and dependability. Implement extensive testing and validation procedures to guarantee the AI system's accuracy and dependability.
- 12. Revolutionizing energy usage in smart buildings Maximizing energy use and operational effectiveness Lowering ecological imprint of buildings Improving energy efficiency and sustainability
Editor's Notes
- Today, I'll present a breakthrough idea that might change the globe. The AI-based Energy Optimization for Smart Building in Oakland City project uses AI to solve environmental issues and achieve long-term energy sustainability. This initiative emphasizes energy efficiency as a key to environmental protection and carbon reduction. We know this is urgent, therefore we must act. We use cutting-edge AI technology to transform how buildings use and manage energy to improve sustainability and reduce our environmental impact. AI-based energy optimization is our focus. This will reduce building energy use, saving resources and reducing waste. We can improve energy use by evaluating data and making smart judgments.
- AI-optimized Oakland energy. Smart buildings use energy, HVAC, and lighting technologies. These inventions may reduce energy and waste. Buildings waste energy. Waste boosts operational costs. Traditional building management systems seldom optimize energy use dynamically. Pollution and expensive electricity consequences. AI-based energy optimization anticipates energy demand, optimizes energy consumption, and analyzes real-time data. We plan. Energy efficiency reduces greenhouse gasses. Energy conservation aids climate aims. Our proposal matters economically. Operator profitability and competitiveness grow with energy efficiency. AI-based energy management systems save power costs, freeing up funds for building maintenance, infrastructure upgrades, and environmental initiatives. Energy-efficient homes appeal as energy costs climb. We help sustainable investors and renters.
- AI helped us improve smart building energy usage. Feasibility studies validated our technical and economic concerns. Stakeholder needs determined this project's success. Plans worked. Data, AI algorithms, and building infrastructure integration were explored. Energy efficiency and performance metrics ensure demonstrable effect. Procurement, risk management, and communication were deliberately tailored for AI's difficulties and potential. AI-integrated execution. Carefully chosen and tuned smart building energy optimization AI models and algorithms. Software allows data analysis, predictive modeling, and informed decision-making. Building management systems provided real-time data. Monitoring and control ensured system efficacy. Carefully placed energy sensors and meters. Our AI forecasts energy demands and optimizes energy use. Building technicians and operators upgraded our AI-based technology.
- Safe projects. Scope, necessity, and estimate are technological dangers. Our project requires everything. Clear requirements and project-based estimates mitigate technical risks. Algorithms and AI optimize energy. Level 1 elevates management risks. Risks include project time, stakeholders, resource allocation, communication, and risk allocation. Project management organizes tasks. Stakeholder involvement and setbacks need realistic timeframes. Risk, communication, and project efficiency interact. Business risks. Internal procurement, supplier/vendor management, and subcontracts are contractual risks. Read contracts to avoid business issues. Internal purchasing is fast and cheap. Supplier/vendor management guarantees quality. Subcontracting decreases outsourcing risks and improves performance. Level 2. Joint ventures, regulation, currency rates, and consumer stability are hazards. Reliable customers. Partnerships lessen dependence. Updating prevents legal issues. Finally, currency rate management stabilizes international project finances and reduces risk.