IoT Backend for Solar SCADA Data Ingestion

@Prutheus

TWINPRO SCADA Ingestion first, plant connection later — starting on a simulator is the sensible order, because it lets the tag mapping and the data-quality rules be proven before real inverters are in the loop. Plan: - FastAPI for REST intake plus an MQTT subscriber, both writing through one normalisation layer, so a tag behaves identically regardless of transport. - PostgreSQL with TimescaleDB hypertables for the raw telemetry, continuous aggregates for the 1-min, 5-min, hourly and daily rollups. Rollups stay correct when late data backfills. - Device/tag mapping held as configuration: device type, vendor tag, canonical point, unit, scale. New inverter model becomes a config row, not a code change. - Quality flags written alongside each sample — missing, stale, out-of-range, frozen-value — so downstream KPIs can exclude bad data instead of silently averaging it. - Configurable SCADA simulator generating multiple days across inverters, weather station, meter and transformer, including deliberate gaps and spikes to test the flags. Background: 24/7 Airflow data pipelines for industrial clients and a Postgres analytics platform ingesting 14 upstream sources. Time-series and messy-source data is the work I do most. Question: what retention do you need at raw 1-minute resolution before downsampling? Martin

@alluankit01

TWINPRO SCADA Hi, I can develop the Solar SCADA / IoT telemetry ingestion backend for TwinPro, including REST/MQTT input, flexible device/tag mapping, time-series storage, aggregations, historical APIs, and a configurable solar plant simulator. The best solution is to first define the device hierarchy, tag model, telemetry format, timestamp rules, data quality flags, and API requirements. Then I’ll build a device-independent ingestion service so new inverter, meter, weather station, SCB, or transformer manufacturers can be added through configuration instead of rewriting the core service. I’m comfortable with Python, MQTT, REST APIs, PostgreSQL/TimescaleDB, IoT telemetry pipelines, SCADA-style data ingestion, time-series aggregation, missing/bad data handling, solar data simulation, and API documentation. Deliverables will include: * Telemetry architecture and tag model * REST/MQTT ingestion service * PostgreSQL/TimescaleDB setup * Raw telemetry storage * 1-min, 5-min, hourly and daily aggregation * Missing/bad data detection * Data quality flags * Historical telemetry APIs * Configurable SCADA simulator * Realistic solar sample data * Setup documentation I’ll focus on a scalable, device-independent backend that can start with simulated solar data now and later connect smoothly to real solar plant equipment. Best regards Ankit

@JoseRCarvas

Hi — this is exactly my stack: Python, PostgreSQL/TimescaleDB, MQTT and REST APIs. You need a telemetry ingestion service that runs on a simulated SCADA feed now and connects to real plants later, across inverters, weather stations, meters, transformers and SCBs. Plan: - Ingestion service accepting MQTT (topic per device/tag) and REST, with a flexible device/tag mapping layer so new equipment types are configuration, not code. - Time-series storage in TimescaleDB hypertables — timestamped, indexed by asset + tag. - Aggregations at 1-min, 5-min, hourly and daily (continuous aggregates). - Data-quality checks: missing/gap detection, out-of-range and frozen-value flags, stored as quality flags alongside each series. - Retrieval APIs for historical telemetry by asset, tag, time range and resolution. - Configurable SCADA simulator generating realistic multi-day data (day/night irradiance curve, ramps, occasional faults) so the whole pipeline is verifiable end-to-end without any hardware. Everything validated against the simulator before real-plant cutover. Deliverables: service code, Timescale schema/migrations, API docs, the simulator + sample datasets, and tests. Quick questions: preferred MQTT broker (Mosquitto / EMQX?), and rough scale (inverters x tags x plants) so I size retention and aggregation correctly. I can also take on the KPI/alarm engine and the React integration if useful. Rating: 5.0 stars. — Ricardo

@NEHABHAT92

TWINPRO SCADA - as a seasoned developer with 9+ years of experience, I am confident that I would be the ideal candidate for your project. Prior to this, I've worked on numerous IoT projects including the development of telemetry ingestion systems and solar SCADA data enrichment systems. Python and PostgreSQL have been my trusted companions in these projects, helping deliver scalable solutions that seamlessly integrate new inverters or sensors, which aligns perfectly with your device-agnostic requirement. MQTT and Modbus are also well within my skillset and have been integral to the success of several previous IoT projects I've worked on. Regarding missing SCADA values, I plan on employing a meticulous approach that involves careful tagging and thorough validation, hence ensuring optimal accuracy for all your data sets. One other plus; my team and I have gained deep insights from working with renewable energy data before. We understand the distinctive data patterns such as cloud-induced variations, power fluctuations, among others that are inherent to solar plants. Trust me to deliver a comprehensive solution; from developing your telemetry architecture to creating a configurable SCADA simulator and even aggregating your historical-data APIs with the added feature of robust documentation. Let's get started!

@sandipm1307

TWINPRO SCADA, trust me, as an experienced Automation Engineer with prowess in IoT and SCADA systems. I have a track record of successful projects that bear similarities to your desired outcome. I specialize in leveraging MQTT for data transfer and device integration - a skill that would prove invaluable for your backend development. My ability to integrate process_logically with industrial hardware like PLCs and HMIs using Modbus TCP/RTU will be particularly useful for this project. For efficient data storage and retrieval, I would recommend employing PostgreSQL's time-series extension TimescaleDB. This solution guarantees robust handling of the flexible dataset that will arise from the various solar plant components. Additionally, my knowledge of clean scripting practices using Python will ensure a reliable and efficient codebase. In terms of past experiences with renewable energy data, I have worked with similar projects in automating data ingestion from solar inverters, smart meters, and weather stations. Furthermore, to address your concern about missing SCADA values or dropped communication connections, my established practices include implementing redundant-systems or error flags that notify the system administrator

@winston052790

Hello, I am writing to express my interest in the IoT Backend for Solar SCADA Data Ingestion position at your company. With my strong background in Python, Cloud Computing, PostgreSQL, Software Development, MQTT, Internet of Things (IoT), Data Analysis, and API Development, I am confident in my ability to develop the telemetry ingestion service for TwinPro. I have previous experience working on IoT/SCADA projects, extensive knowledge of MQTT/Modbus, and expertise in handling missing SCADA values. I am familiar with renewable energy data and have the skills necessary to successfully complete this project. I am excited about the opportunity to contribute to the development of TwinPro and look forward to discussing my qualifications further. Thank you for considering my application. Sincerely, Winston

@bobs445

TWINPRO SCADA I can help build the telemetry ingestion backend for TwinPro with a device-independent architecture designed for solar SCADA and IoT data processing. I have experience developing Python backend systems, IoT data pipelines, API services, database architectures, and real-time data processing solutions. I can design a flexible ingestion service that supports REST and MQTT inputs, configurable device/tag mapping, and future integration with different inverter and sensor manufacturers without rewriting the core system. For the architecture, I would use Python with FastAPI, MQTT communication, and PostgreSQL with TimescaleDB for efficient time-series storage. The system will support raw telemetry storage, aggregation intervals, historical data APIs, and data quality tracking for missing or invalid values. I can handle SCADA challenges such as missing telemetry, communication failures, invalid sensor readings, and equipment alarms by implementing validation rules, timestamps, quality flags, and recovery mechanisms. I can also develop a configurable solar SCADA simulator that generates realistic plant behavior including sunrise/sunset patterns, production curves, weather fluctuations, inverter derating, alarms, and communication issues. I will deliver the ingestion service, database design, simulator, APIs, documentation, and a scalable foundation ready for real solar plant integration.

@gkcodelabs

TWINPRO SCADA You need one ingestion path that works whether the source is your simulator today or real Modbus/MQTT inverters, meters and weather stations next month — the part that'll bite is hardcoding parsers per device brand, since adding a manufacturer should mean config, not a rewrite. Quick one: do you already have a register map or MQTT topic structure from a target device, or should M1's tag model be scoped off the simulator for now? - SCADA/IoT: no branded SCADA project yet, but we run high-volume Kafka/Spark Structured Streaming ingestion daily — same shape of problem. - MQTT/Modbus: MQTT maps onto our streaming background; Modbus we'd treat as config, not custom code per device. - Time-series DB: TimescaleDB — hypertables + continuous aggregates give native minute/hourly/daily rollups on plain Postgres. - Missing data: every reading gets a quality flag (good/stale/missing/ interpolated); short gaps forward-fill, longer gaps stay flagged, never fabricated. - Renewable energy: not sector-specific yet — cyclical output, dropout, derating are familiar patterns. M1 (day 2): tag model + architecture. M2 (day 3): ingestion API + MQTT live on simulator data. M3 (day 4): TimescaleDB schema + hypertables running. M4 (day 6): SCADA simulator — day/night curve, cloud noise, faults, comms drops. M5 (day 7): aggregation + historical APIs + docs. Milestone-gated payments — each stage runs before you release the next. — Arpit, GKCodeLabs

@CliveMSoftware

TWINPRO SCADA. I've built multiple IoT telemetry platforms handling real-time sensor data ingestion via REST and MQTT, with particular experience in renewable energy monitoring systems. For your project, I'll architect a flexible tag-mapping layer that lets you onboard new inverter manufacturers and sensors through configuration alone, then develop the dual-path ingestion service supporting both REST and MQTT protocols. I recommend TimescaleDB for its superior time-series performance and native PostgreSQL compatibility, and I'll implement your aggregation pipeline (1-min through daily) with data quality flagging for missing/anomalous values. The SCADA simulator will generate multi-day datasets with realistic solar curves, cloud effects, equipment faults, and communication dropouts. All components will be delivered with clean APIs and full documentation across your five milestones within the 7-day window.

@bohdanmelnykua

TWINPRO SCADA. Hi! I have built telemetry ingestion services before - REST and MQTT intake, tag mapping, aggregation into Postgres/Timescale - though not specifically for solar plants yet. I can put together the ingestion API, simulator and aggregation layer in about 6 days. Do you already have a preferred MQTT broker, or should I set one up as part of this?

@rahulk0744

TWINPRO SCADA As an experienced Senior Full-Stack & Mobile App Developer, I bring the ideal blend of skills to create your Solar SCADA / IoT Telemetry Data Ingestion Backend. My extensive knowledge in Python is a game-changer for this project, especially in terms of supporting REST and the MQTT input that is essential for a successful telemetry ingestion service like yours. Working with PostgreSQL/TimescaleDB will be a breeze as it is one of my preferred databases for time-series data. Regarding your concerns about handling missing SCADA values, I firmly believe in proactive system design. I will implement data quality flags and generate missing data reports so they can be rectified promptly, avoiding any disruptions. In addition, my previous experience on various IoT projects equip me with an understanding of renewable-energy data and its unique challenges making me ready to tackle the needs on this mission critical backend project. To ensure you can add more inverters or sensors without re-writing the complete ingestion service, I will utilize my expertise in building highly-configurable systems. Rather than spending resources on overhauling the codebase whenever you need to integrate new devices; you’ll have a flexible and easily customizable service.

@milanc46

TWINPRO SCADA Hey there, I understand you're looking for an experienced IoT backend developer to build a scalable, device-independent telemetry ingestion platform for your TwinPro solar SCADA solution. Tech Stack: ■ Python, FastAPI, MQTT, REST APIs ■ PostgreSQL, TimescaleDB, Redis ■ Modbus, IoT Telemetry & SCADA Integration ■ Docker, AWS, Cloud Deployment Answers: ■ Previous IoT/SCADA Projects: Delivered IoT monitoring platforms for industrial automation, energy monitoring, remote telemetry, and connected embedded devices. ■ MQTT/Modbus Experience: 5+ years of experience integrating MQTT brokers, Modbus RTU/TCP, and real-time telemetry systems. ■ Recommended Database: TimescaleDB on PostgreSQL for efficient time-series storage, querying, and aggregation. ■ Handling Missing SCADA Data: Timestamp validation, data quality flags, configurable interpolation, and missing-data detection with alerts. ■ Renewable Energy Experience: Y es, we've worked on IoT platforms for solar monitoring, energy management, and industrial telemetry. Query: Will the first phase require authentication (API keys/JWT) for telemetry ingestion, or can this be added later? Guarantee: ■ End-to-end technical support ■ Transparent communication ■ Regular progress updates ■ Clean and production-ready solution Let's connect, and I'll walk you through relevant projects while discussing the best architecture for TwinPro. Regards, Milan

@sandeepmishra01

**TWINPRO SCADA** Hello, I have **14+ years of experience** in IoT, Azure Cloud, .NET, microservices, and telemetry data processing. I have built scalable backend systems for real-time device communication and monitoring. For your project, I can deliver: * REST/MQTT telemetry ingestion service * Flexible device/tag mapping (device-independent design) * Time-series data storage using PostgreSQL/TimescaleDB * 1-minute, 5-minute, hourly, and daily aggregations * Data quality checks for missing/invalid telemetry * Historical telemetry APIs * Configurable SCADA simulator with realistic solar plant behavior (day/night cycle, cloud effects, alarms, communication failures, inverter derating) **Database Recommendation:** PostgreSQL with TimescaleDB for efficient time-series storage and querying. **Missing Data Handling:** Missing or invalid values will be flagged with quality indicators while preserving raw telemetry for analysis. Although I haven't worked directly on a renewable-energy project, I have extensive experience building IoT and telemetry platforms and can quickly adapt to solar SCADA requirements. I am committed to delivering a clean, scalable, and well-documented solution. Thank you.

@VutomiM1

TWINPRO SCADA We recently helped a business achieve a similar goal, and the results exceeded their expectations. I'd love to help you do the same. I’ll build a solution that’s reliable, professional, and designed to help your business grow. My experience with IoT and SCADA projects, specifically in creating data ingestion services, positions me perfectly for this task. Your project stood out because you're focused on a clean, professional telemetry solution, and that’s exactly the kind of work I enjoy. I have extensive experience with MQTT and PostgreSQL, ensuring robust data handling and storage. We have 75+ 5-star reviews on similar projects and rank in the top 1% among 75 million users! I’d be happy to share a few ideas for your project and answer any questions you have. Regards, Vutomi

@nanisem

**TWINPRO SCADA** I recently assisted in transforming a concept into a sophisticated digital experience, focusing on modernity and user-centric design. I can help you develop a robust telemetry ingestion service that not only meets your technical requirements but also enhances overall operational efficiency. I understand you're looking for a solution that is clean, professional, and seamless, with a strong emphasis on usability and flexibility for future device integration. I specialize in crafting scalable backends for IoT applications, ensuring smooth data ingestion and real-time monitoring. My past experience includes developing a telemetry ingestion service for a solar power application, which you can review here: [Culture City Web Application](insert-your-link-here). I am eager to discuss your project and explore how I can assist you in achieving your objectives. The only thing you will lose is some time on a free consultation. Kind Regards, Nanise Mostert

@abhijitk48

Hello, I am a Backend Developer with experience in building REST APIs, database-driven applications, and scalable backend systems. I can develop the telemetry ingestion service with a modular and device-independent architecture. For this project, I would: Build REST API and MQTT-based telemetry ingestion. Implement configurable device/tag mapping. Store raw telemetry in PostgreSQL/TimescaleDB. Create 1-minute, 5-minute, hourly, and daily aggregations. Handle missing and bad data using quality flags. Develop a configurable solar SCADA simulator with realistic generation patterns, alarms, communication failures, and inverter derating. Build APIs for historical and aggregated telemetry retrieval. Recommended Database: PostgreSQL with TimescaleDB for efficient time-series data storage. Missing Data Handling: Missing values will be stored with quality flags, ti

@satvikahuja20

TWINPRO SCADA I can develop a robust, device-independent telemetry ingestion backend for TwinPro, including REST/MQTT ingestion, configurable tag mapping, time-series storage, aggregation, data-quality handling, and historical APIs. I have experience with Python-based backend development, IoT data pipelines, PostgreSQL, real-time telemetry, API development, and integrating hardware/sensor data. I can structure the system so that new inverter, meter, weather-station, SCB, or transformer manufacturers can be added through configuration rather than modifying the core ingestion logic. For the architecture, I recommend Python (FastAPI) for the ingestion/API layer, MQTT for real-time telemetry, and PostgreSQL with TimescaleDB for efficient time-series storage and aggregation. Missing/bad SCADA values will be handled using timestamps, validation rules, quality flags, gap detection, and clear separation between raw and processed data. Aggregation can support 1-minute, 5-minute, hourly, and daily intervals while preserving raw telemetry for auditing. I can also build a configurable solar SCADA simulator capable of generating realistic multi-day plant data, including sunrise/sunset behavior, irradiance variations, cloud effects, inverter derating, alarms, communication failures, and missing values. I will deliver the project milestone-by-milestone with clean architecture, documentation, APIs, database schema, and deployment instructions.

@barakadevx

Hello, I am a skilled software developer with experience in React.js, Node.js, JavaScript, MongoDB, MySQL, PHP, and responsive web development. I can build a clean, modern, secure, and user-friendly solution that meets your requirements. I pay close attention to details, communicate clearly, and deliver quality work on time. I would be happy to discuss your project and get started. Thank you.

@ashrafa275

Hi there, I am a Systems & Software Engineer with strong experience in IoT telemetry, Python backends, FastAPIs/Flask, MQTT brokers, and time-series DB design. I can build a device-independent telemetry ingestion backend for TwinPro. 1. Experience: Built telemetry backends and embedded IoT devices using Python, MQTT (Mosquitto), and REST APIs to log real-time sensor/power data. 2. Recommended Time-Series DB: TimescaleDB (PostgreSQL extension). It offers standard SQL flexibility with hypertables and continuous aggregations (1-min, 5-min, hourly, daily) for millions of solar data points. 3. Handling Missing/Bad Data: - Validation: Schema layer checks bounds (e.g., active power within rated capacity). - Quality Flags: Out-of-bound or missing readings are flagged (`GOOD`, `BAD`, `MISSING`). - Analytics: Forward-fill / linear interpolation during aggregation without altering raw telemetry. 4. Flexible Tag Mapping: JSON-based mapping allowing you to add new inverter models by configuration without code changes. 7-Day Milestones Plan: - M1: Telemetry Architecture & Tag Mapping Config - M2: REST/MQTT Ingestion Pipeline & Quality Flagging - M3: TimescaleDB Setup with Aggregation Views - M4: Realistic Solar SCADA Simulator (Day/Night, clouds, faults) - M5: Historical Retrieval APIs & Documentation Ready to start immediately! Best regards, Achraf