Individual research contributions to group project

- Research on different areas that required improvement for the civil engineering industry

- Researched on real time structural health monitoring sensors (below are the listed advantages and disadvantages in the different areas)

- Collaborated with team members to share our different areas of research to determine which of our topics was the most feasible, desirability, viability.

-Conducted further background research on excavators and what areas could be improved technologically

-Identified gaps in research as to how this technology could bring about greater efficiency in the sector

-Participated in group discussions and gave input as to how feasible technology was

-Set reminders and actively checked on progress of group to stay on track and ahead of deadline

-Wrote sections 1.14, 1.2 & 1.3 in CA2 report

	Advantages	Disadvantages
Feasibility	Technology Availability: Sensors and monitoring systems are becoming more advanced and affordable, making it easier to implement SHM.	Initial Setup: Initial setup can be complex and expensive due to the need for specialized sensors and equipment.
	Data Collection: Continuous, real-time data allows for better understanding of structural performance under varying conditions.	Retrofitting Challenges: Infrastructure can be difficult to retrofit with sensors, especially in older or hard-to-access structures.
	Maintenance: Automated systems can reduce human labor required for manual inspections.	Infrastructure Requirements: Requires infrastructure that supports data transmission (e.g., wireless networks), which can be challenging in remote locations.
Viability	Cost Efficiency (Long-Term): Can save on maintenance and repair costs by identifying issues early, preventing major failures.	High Initial Investment: High initial capital investment for sensor installation, network setup, and data infrastructure.
	Data-Driven Decision Making: Provides engineers with actionable insights, allowing for proactive maintenance and extending infrastructure lifespan.	Ongoing Costs: Ongoing costs for data storage, analysis, and system maintenance may become a financial burden.
	Resource Optimization: Allows for optimized resource allocation by focusing repairs and maintenance on areas most in need.	Expertise Required: The effectiveness of data analysis depends on the quality of the sensors and the expertise required to interpret the data.
Desirability	Safety: Improves safety by providing early warnings of structural issues, potentially preventing catastrophic failures.	Over-Reliance on Automation: Could create over-reliance on automated systems, potentially ignoring other signs of degradation that sensors may miss.
	Sustainability: Promotes longer lifespans for infrastructure, reducing the need for frequent repairs or replacements.	Data Management Complexity: Complexity in managing large-scale networks of sensors and interpreting vast amounts of data.
	Public Confidence: Increases public trust in infrastructure by demonstrating proactive efforts to monitor and maintain structural health.	Privacy and Security Concerns: Public concern over privacy or data security, especially if the data is shared with external parties or companies.