Noobies Project

Team Name

Noobies

Team Members

Project Description

How to open our project:
we work on rapid miner so when you go to evidence of work there is a file with.rmp at the tail. Please open it in Rapidminer(altar studio) , when you open file you will see the 3 read CSV named Alpha X, atmost, Dingtek , they are our chosen 3 datasets(similar names). you need to double click on each of them and open each dataset of us( dataset we selected). and all done click the enter button. if you have any misunderstanding please call me: 0422 953 002

Project Description:
Analysis of Visitor, weather, vehicles,…at Sugar Bag Road Town Reserve to choose the best time to do the infrastructure maintainance

In this project, we conducted an analysis of various datasets collected from the Sugar Bag Road Town Reserve, focusing on the relationship between weather conditions and visitor patterns. The primary objective was to understand how different weather conditions, such as temperature fluctuations, impacted the number of visitors, occupancy levels, and device connectivity within the reserve.

Datasets and Methodology:

Visitor Data: We utilized data from the Milesight Occupancy Counter and Farmo PIR Counter, which recorded the number of visitors to the reserve over time. This data was visualized to observe trends and peaks in visitor numbers.
Weather Data: Data from the Atmos Weather Station, including temperature readings, was analyzed alongside visitor data to identify correlations between weather conditions and visitor behavior.
WiFi Connectivity Data: The NCount WiFi Counter provided insights into the number of devices connected within the reserve, serving as a proxy for visitor engagement and presence.
Findings: Through our analysis, we observed a clear pattern indicating that adverse weather conditions, particularly lower temperatures, had a significant impact on visitor numbers. Specifically:

On days with lower temperatures, the number of visitors recorded by the occupancy counter and PIR counter was noticeably lower.
Similarly, the number of devices connected to the WiFi network within the reserve also decreased during colder weather, suggesting that fewer people were spending time in the area.
These findings highlight the strong correlation between weather conditions and visitor behavior at Sugar Bag Road Town Reserve. Understanding these patterns can help in planning and managing the reserve, particularly in terms of resource allocation and visitor services during different weather conditions.

Project Description: Analysis of Visitor Patterns at Mary Cairncross Scenic Reserve
Our project involved analyzing various datasets to understand the relationship between weather conditions and the activity levels within a specific area, as measured by the number of people, connected devices to the Wi-Fi, and the occupancy count at the center. Through our analysis, we found a clear correlation between adverse weather conditions, particularly low temperatures, and decreased activity levels.

We discovered that when the temperature drops, there is a noticeable decline in the number of people visiting the area, as well as a reduction in the number of devices connected to the Wi-Fi network. This trend was consistent across different weather conditions

--> with the clustering Model, we have many clusters of Cars, people, Air temperature and wind direction,… with Y axis is datetime, we can predict the best time to do maintenance, the time with least people in there in a good weather condition

Data Story

Sugar Bag Road Town Reserve, known for its scenic mountain bike tracks, has been experiencing a surge in visitor numbers. While this influx has brought economic and recreational benefits, it has also posed significant challenges. The increased foot and bike traffic, coupled with heavy rainfall, has accelerated the wear and tear of the trails, leading to issues such as track erosion. Additionally, the need for ongoing maintenance has placed considerable strain on the council's budget, making it imperative to find efficient ways to manage and mitigate these impacts.

To address these challenges, a series of Internet of Things (IoT) sensors were strategically deployed across the park and trails to monitor various factors influencing the park's usage and condition. These sensors include:

Weather Station: Provides real-time data on temperature, humidity, wind speed, rainfall, and solar irradiance.
WiFi Probe Counter: Tracks the number of connected devices in the car park area and monitors dwell time.
Object Detection Cameras: Count and categorize the number of people, vehicles, and bikes in the car park, at major track entrances, and in the café area, without capturing any private information.
Passive Infrared Bi-Directional Counters: Use heat signatures to identify and count people passing along the tracks, including their direction of movement.
Passive Infrared Counters: Count the number of people entering and exiting two amenities facilities and three additional trails.
Vibration Counters: Monitor the number of bikes crossing two trail challenges.
The Data Journey: From Collection to Insight
Our project began with the collection of extensive datasets from these IoT sensors. The data spanned several months, capturing key metrics such as weather conditions, visitor numbers, and trail usage patterns. However, raw data is often messy and requires careful cleaning and preparation before meaningful insights can be drawn.

Using RapidMiner, a powerful data analytics platform, we embarked on the process of cleaning and transforming the data. This involved:

Data Cleaning: Removing any inconsistencies, missing values, and outliers that could skew the analysis. This step ensured that the data was accurate and reliable for further examination.

Data Integration: Merging data from different sensors into a cohesive dataset, enabling us to explore relationships between various factors, such as weather conditions and visitor numbers.

Data Visualization: Creating visual representations of the data to uncover trends and patterns. Graphs, charts, and heat maps were generated to illustrate the correlation between weather events and visitor behavior, track usage, and the resulting wear and tear.

Key Insights: The Weather-Visitor Relationship
Through our analysis, a clear pattern emerged: weather conditions significantly influenced visitor numbers and trail usage. Specifically:

Temperature and Rainfall: On days with lower temperatures or higher rainfall, visitor numbers noticeably decreased. This was evident from the occupancy counters, which recorded fewer people on the trails during adverse weather conditions.

Device Connectivity: The WiFi probe counter showed a decline in the number of connected devices in the car park area on colder days, further supporting the observation that fewer people were present in the reserve.

Trail Usage: The passive infrared counters and vibration counters also reflected reduced activity on the trails during bad weather, indicating a direct link between environmental factors and trail usage.

Implications and Future Directions
These findings have important implications for the management of Sugar Bag Road Town Reserve. Understanding the relationship between weather conditions and visitor behavior allows for better planning and resource allocation. For example:

Maintenance Scheduling: Maintenance efforts can be optimized by aligning them with periods of low visitor activity, reducing disruptions and ensuring the trails are in good condition during peak times.

Budget Allocation: By predicting visitor patterns based on weather forecasts, the council can better allocate resources and manage the budget more effectively, focusing on critical maintenance needs when visitor numbers are expected to be high.

Visitor Experience: Enhanced understanding of visitor behavior enables the development of strategies to improve the overall visitor experience, such as providing more sheltered areas or temporary facilities during unfavorable weather conditions.

In conclusion, the integration of IoT sensor data and advanced analytics has provided valuable insights into the dynamics of visitor impact at Sugar Bag Road Town Reserve. By continuing to monitor these patterns, we can ensure the sustainability and enjoyment of this natural asset for years to come.

Data Story: Analyzing Visitor Behavior at the Mary Cairncross Scenic Reserve

Introduction: The Mary Cairncross Scenic Reserve, a 55-hectare subtropical rainforest in Maleny, is not only a haven for biodiversity, housing 391 plant species, 141 bird species, and 68 species of mammals, reptiles, and amphibians, but it is also a site that benefits from cutting-edge data analytics. Through the installation of multiple sensors, the reserve gathers comprehensive data on both environmental conditions and visitor behavior. These insights are critical for efficient visitor management and understanding the impacts of seasonal and climate changes on the reserve's delicate ecosystem.

Data Collection: To monitor and analyze the reserve's environment and visitor activities, a variety of sensors were strategically installed throughout the area:

1 Weather Station: Measures weather conditions, including temperature, humidity, and gust speed.
1 WiFi Probe Counter: Captures the number of devices connected to the Wi-Fi, providing a proxy for visitor count.
1 Object Detection Camera: Tracks the movement and number of vehicles in the carpark.
3 Passive Infrared Bi-Directional Counters: Monitor foot traffic, counting the number of people entering and exiting specific areas.
3 Passive Infrared Counters: Measure overall people movement within the reserve.
1 Soil Moisture Sensor: Measures soil moisture and temperature, crucial for understanding plant health.
2 Environment Monitoring Systems (EMS): Track ambient temperature and humidity.
6 Temperature Probes: Measure the temperature of BBQ facilities, helping to determine their usage.
Key Findings:

Correlation Between Weather and Visitor Numbers: Our analysis revealed that adverse weather conditions, particularly lower temperatures, significantly reduce the number of visitors to the reserve. The scatter plot titled "Gust Speed effects on people visiting" illustrates that as gust speed increases, the number of visitors decreases. Similarly, the graph titled "Temperature effect on Visitors" shows a clear trend where visitor numbers peak around 23-24°C and decline as temperatures rise or fall outside this range.

Visitor Engagement with Amenities: The data indicates a strong correlation between the number of vehicles in the carpark and the number of visitors utilizing the reserve’s amenities. This suggests that higher visitor numbers lead to increased use of the bike tracks, BBQ facilities, and other amenities, reinforcing the need for adequate resource allocation during peak times.

Impact of Environmental Conditions: Beyond just visitor behavior, the sensors provide valuable insights into the environmental conditions of the reserve. For example, the soil moisture sensor and EMS data help track the effects of climate and seasonal changes on the reserve's ecosystem. Understanding these patterns is crucial for the conservation of the reserve's diverse plant and animal species.

Occupancy Trends: The installation of passive infrared counters revealed fluctuations in the reserve's occupancy levels throughout different times of the year. Peaks in visitor numbers were often aligned with favorable weather conditions, while dips corresponded with colder or more extreme weather. This information is vital for planning staffing levels, resource management, and conservation efforts.

Conclusion: The integration of sensor technology at the Mary Cairncross Scenic Reserve has provided deep insights into both visitor behavior and environmental conditions. The data underscores the importance of monitoring weather patterns and their influence on visitor turnout, as well as the need for targeted management of the reserve’s amenities to ensure a positive visitor experience. Additionally, understanding the environmental conditions that affect the reserve's biodiversity is essential for its long-term preservation. These insights will continue to guide sustainable visitor management and conservation strategies, ensuring that the Mary Cairncross Scenic Reserve remains a cherished natural sanctuary for future generations.