SE4CPS/PlantWaterSystem
Feb 2025 – Apr 2025
3 Months active
Languages Used
BashMarkdownPythonShellXMLDockerfile
Technical Skills
API IntegrationDevOpsDocumentationEmbedded SystemsError HandlingFlask
MayureshMore
PROFILE
Mayureshmore
Developed and enhanced the SE4CPS/PlantWaterSystem, focusing on end-to-end sensor data acquisition, real-time scheduling, and automated deployment for IoT-based irrigation management. Leveraged Python and Shell scripting to integrate soil moisture sensors with Raspberry Pi devices, enabling reliable data collection, local storage, and secure transmission to a backend API. Introduced modular code structure, Docker-based containerization, and systemd service updates to streamline provisioning and ongoing maintenance. Implemented robust error handling and retry logic to improve reliability, while integrating a Weather API module to support data-driven irrigation decisions. The work emphasized maintainability, operational efficiency, and scalable onboarding across embedded field devices.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
15Total
Bugs
0
Commits
15
Features
4
Lines of code
125,804
Activity Months3
Your Network
25 peopleSame Organization
@u.pacific.edu16
Shared Repositories
9
Ashok SravanamMember
Cheng-Han-ChungMember
Nakul BhandareMember
ravikthMember
Solomon BerheMember
sob05001Member
TinzzsMember
Cheng-Han-ChungMember
Vy NguyenMember
Work History
April 2025
2 Commits • 1 Features
Apr 1, 2025Month: 2025-04 | Repository: SE4CPS/PlantWaterSystem | Overview: Delivered embedded Plant Water System enhancements with real-time sensor data collection, scheduled one-minute transmissions, local storage, and backend integration. Added deployment utilities, a Weather API module, and deployment scripts to streamline provisioning and updates. No formal bug fixes reported this month; reliability improvements implemented via robust error handling and transmission retries. Impact: improved data fidelity and near real-time monitoring, enabling proactive irrigation decisions and easier device management. Technologies/skills demonstrated: embedded systems development, real-time scheduling, error handling, secure backend API integration, deployment automation, and Weather API integration.
2 Commits • 1 Features
Apr 1, 2025Month: 2025-04 | Repository: SE4CPS/PlantWaterSystem | Overview: Delivered embedded Plant Water System enhancements with real-time sensor data collection, scheduled one-minute transmissions, local storage, and backend integration. Added deployment utilities, a Weather API module, and deployment scripts to streamline provisioning and updates. No formal bug fixes reported this month; reliability improvements implemented via robust error handling and transmission retries. Impact: improved data fidelity and near real-time monitoring, enabling proactive irrigation decisions and easier device management. Technologies/skills demonstrated: embedded systems development, real-time scheduling, error handling, secure backend API integration, deployment automation, and Weather API integration.
April 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for SE4CPS/PlantWaterSystem focusing on core improvements, deployment readiness, and maintainability across devices. The work lays the foundation for scalable onboarding, reliable telemetry, and streamlined operations.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for SE4CPS/PlantWaterSystem focusing on core improvements, deployment readiness, and maintainability across devices. The work lays the foundation for scalable onboarding, reliable telemetry, and streamlined operations.
February 2025
12 Commits • 2 Features
Feb 1, 2025February 2025 (SE4CPS/PlantWaterSystem) focused on delivering end-to-end sensor data capture from soil moisture sensors and automating Raspberry Pi deployments to accelerate field-ready deployments. Key outcomes include a robust soil moisture data pipeline integrated with the backend API, and a repeatable, documented Raspberry Pi onboarding process with automation scripts and I2C enablement. While no major bugs were opened, the work established a scalable edge-to-backend data flow and reduced manual setup time significantly. The initiatives improve data-driven irrigation decisions and operational efficiency for field deployments, with measurable improvements in deployment speed and system reliability.
12 Commits • 2 Features
Feb 1, 2025February 2025 (SE4CPS/PlantWaterSystem) focused on delivering end-to-end sensor data capture from soil moisture sensors and automating Raspberry Pi deployments to accelerate field-ready deployments. Key outcomes include a robust soil moisture data pipeline integrated with the backend API, and a repeatable, documented Raspberry Pi onboarding process with automation scripts and I2C enablement. While no major bugs were opened, the work established a scalable edge-to-backend data flow and reduced manual setup time significantly. The initiatives improve data-driven irrigation decisions and operational efficiency for field deployments, with measurable improvements in deployment speed and system reliability.
February 2025
Activity
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Quality Metrics
Correctness88.0%
Maintainability85.4%
Architecture83.4%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashDockerfileMarkdownPythonShellXML
Technical Skills
API IntegrationData AcquisitionData ManagementDatabase ManagementDeploymentDevOpsDockerDocumentationEmbedded SystemsError HandlingFlaskHardware IntegrationIoTPythonRaspberry Pi
Repositories Contributed To
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