AI Surveillance Person Detection System

@kamran2012

Hi there, I will build your AI surveillance pipeline - person detection model fine-tuned for your three environments, a Python service that ingests RTSP streams and triggers your webhook on detection, and a facial recognition layer that matches against your watch-list in real time. For handling the mixed conditions, I will train with augmented datasets that simulate low-light noise, glare, and rain artifacts so the model holds accuracy without needing separate models per environment. I will use YOLOv8 for detection with DeepSORT tracking to reduce duplicate alerts in high-traffic zones, and run inference optimized with TensorRT on your CUDA server for minimal latency between frame capture and alert. The event recorder will write tagged clips to a structured archive with metadata (timestamp, camera ID, match confidence, face ID if recognized) so retrieval is straightforward through simple queries. Questions: 1) How many RTSP streams will run simultaneously, and what resolution are they outputting? 2) For the watch-list facial recognition, roughly how many individuals will be in the database? Looking forward to discussing further. Thanks and best regards, Kamran

@quan9824

EXPERT in(Computer Vision and Real-time Object Detection, Counting and Tracking) Hi, how are you? I checked your detail carefully. I’ve completed the real-time people detection, counting and tracking projects before successfully. Before, using python and YOLOv8, I completed @@Pool Drowning Detection System Implementation@@ project and so on. You can check my works history on my portfolio. I am sure this field and I will do my best. I always thought "It is your job, it is also my job". Awarding me will be the fastest way to complete your task with the best rates possible. THANK YOU.

@GdevDataSceince

Hi there, I am a Data Scientist and am a professional responsible for extracting actionable insights and knowledge from large volumes of data. As an experienced Data Scientist in the field of machine learning, I am highly proficient in Python and have a deep understanding of algorithms and data structures. My skills make me a great fit for your project as I can guide you through comprehensive coverage of data structures and algorithms while providing patient and thorough explanations. I have over 12-plus years of experience with Python Library Pandas, Karas, TensorFlow, NumPy, PyCharm, Py torch, Open CV, NLP, and others. With over a decade's worth of experience under my belt, including expertise in NLP, Neural Networks, CNNs, RNNs, LSTM, GANs just to mention a few, I can provide you not only with knowledge but also how to apply it efficiently. Partnering with me ensures you have a patient, knowledgeable and skilled tutor who is dedicated to your success in this field. My top priority is to provide a high quality of work, https://www.freelancer.com/u/GdevDataSceince Let's discuss this further via chat, and I'll start your project right now. Thanks Gdev

@ivaylo8

Hi there, I’m Ivaylo, and I’m excited by your vision of an AI-powered surveillance system that detects people in real time, records clean event clips, and selectively recognizes faces against a watch-list. I’ll tailor a robust solution that thrives across low-light, rain, glare, and crowded scenes, running efficiently on your CUDA-enabled Nvidia server. What I’ll deliver: - A finely-tuned computer-vision model (YOLO/TensorFlow/PyTorch) specialized for PIR-style person detection, with high recall and precision under challenging conditions. - A lightweight Python service that ingests RTSP streams, runs detection, triggers your webhook immediately on detections, and archives event clips with consistent tagging for fast retrieval. - Optional facial recognition when image quality allows, with configurable watch-list matching and privacy-safe handling. - Clear setup instructions and a validation report showing performance across night-time, outdoor weather, and high-traffic scenarios. Why this approach works for you: I’ll leverage your existing GPU server, optimize for low-latency inference, and provide modular scripts so you can tweak thresholds, alerting, and archive conventions as needs evolve. I’ll also include a compact API surface so you can extend triggers to other systems with ease. Best regards, Ivaylo

@hotanloc

Hello, I have already completed a similar project successfully. Project review: https://www.freelancer.com/projects/python/people-detection-counting/reviews Please take a look at my previous Freelancer projects and reviews. Your project aligns well with my experience, and I will do my best to meet all your requirements. My core expertise is in object detection, tracking, and counting. I have developed many computer vision projects, including: * People detection and counting * Product detection and counting * Defect detection in manufacturing * Vehicle detection and speed analysis I have strong experience in image processing and CCTV video analysis, where objects are detected and counted from images or video streams. For your project, I will: 1. Train a model using annotated data to generate optimized weights 2. Develop the detection system based on the trained model 3. Analyze detected objects and display the results clearly My technical stack includes YOLO, OpenCV, TensorFlow, PyTorch, Keras, OCR, and other ML/DL frameworks. With my experience in machine learning and deep learning, I can build an accurate detection system and implement post-processing (such as object counting and analysis) using OpenCV. I am confident I can deliver a high-quality solution within a short timeframe. Please feel free to send me a message so we can discuss your project in more detail. I look forward to hearing from you. Thank you.

@amgadmourad18

Hello , I'm an AI engineer and Full stack web developer using python django . i'm a perfect fit for your project , i will create your api and will fine tune your AI detection model . let's start right away .

@Zawiya3

Leveraging my diverse set of skills and expertise, I am ideally suited to deliver the AI Surveillance Person Detection System you need. Having consistently excelled in software development, data science, full-stack engineering, graphic design, cloud architecture, and electronics engineering – I bring a broad perspective to your project. My major strength lies in data science and machine learning - the backbone of developing an AI surveillance system like yours. Specifically with Python, I have executed web scraping and data collection; data preprocessing and analysis; GUI application development; as well as machine learning and deep learning solutions. Importantly, I am well-versed in utilizing YOLO, TensorFlow, PyTorch, OpenCV style platforms required for this project. Further, as an AWS certified professional solutions architect - your CUDA-enabled Nvidia GPU server will be optimally utilised under my aegis.

@nemanjac6

Hello! You’re looking to build an AI surveillance system with person detection, I’d handle it by fine-tuning a YOLO/PT model and deploying a CUDA-accelerated RTSP inference service. This comes down to robust detection under harsh lighting, and I’d solve it by multi‑scenario training and GPU‑optimized preprocessing. A key constraint is maintaining real-time inference across multiple streams without dropping frames. I’ve built similar GPU-backed CV pipelines for night-time and outdoor security, hitting stable sub-100ms latency. I’d structure it like this: - Train/fine‑tune a YOLOv8/YOLOv10 model on mixed‑environment datasets + your watch‑list facial set. - Build a Python service that ingests RTSP streams, runs detections, handles clip extraction, tagging, and triggers your webhook. - Add CUDA‑optimized low‑light enhancement and glare compensation modules. A clever twist is using dynamic thresholding to maintain accuracy across weather and traffic changes. Which RTSP stream throughput (number of cameras + FPS) should the system be engineered to sustain on your Nvidia server? Open to digging into this further. - Nemanja

@HiraMahmood4072

Hello, With over 7 years of experience in Machine Learning (ML) and Python, I have carefully reviewed your requirement for an AI Surveillance Person Detection System. To execute this project, I plan to utilize a combination of YOLO, TensorFlow, and OpenCV to train or fine-tune a computer-vision model that can accurately detect people in real-time across various environmental conditions. The system will be designed to push immediate alerts upon person detection, record and archive the event, and perform facial recognition when appropriate. The deliverables will include trained model files, custom scripts, a lightweight Python API for stream ingestion and detection, setup instructions, and a validation report showcasing performance in low-light, outdoor, and high-traffic scenarios. I am keen to discuss this project further and address any queries you may have. Please connect with me via chat for a detailed conversation. You can visit my Profile: https://www.freelancer.com/u/HiraMahmood4072 Thank you.

@devbaloni1983

Hello, I am a Python Developer with 15+ years of experience in building secure, scalable, and high-performance applications. I specialize in Python-based backend development, automation scripts, API development, data processing, and integrating third-party services. My expertise includes Django, Flask, FastAPI, REST APIs, MySQL/PostgreSQL, and cloud deployment. I also recently worked on integrating the OpenAI API for auto-generated content, images, and automation features—showing my ability to adopt modern AI technologies. If you are looking for a dedicated Python Developer who delivers clean code, reliability, and fast results, I’d be glad to work on your project.

@DngPhgNam

⭐⭐⭐⭐⭐ ✅Hi there, hope you are doing well! I recently completed an AI surveillance system project using YOLO and OpenCV for real-time person detection that worked seamlessly with existing GPU setups. The key to success in this project is finely tuning the model to maintain accuracy across varied lighting and environmental conditions. Approach: ⭕ I will fine-tune a YOLO or equivalent model using diverse datasets reflecting your camera conditions. ⭕ Develop a lightweight Python API that processes RTSP streams and triggers your alert webhook instantly. ⭕ Implement event recording with smart archiving and tagging for efficient retrieval. ⭕ Integrate facial recognition using your watch-list for flagged matches with robust quality checks. ⭕ Provide setup instructions and detailed validation reports under your specified conditions. ❓ Could you specify your preferred facial recognition libraries or frameworks for integration? I am confident my expertise aligns perfectly with your needs and I look forward to delivering a reliable, high-performance system tailored to your security cameras. Kind regards, Nam

@huonghy89

Hi, I hope you are doing well. Very happy to bid your project because my skills are fitted in your project. I have experience building real-time computer vision systems using YOLO/PyTorch and OpenCV, including person detection, facial recognition, and GPU-accelerated video processing pipelines. I will develop and fine-tune a robust model optimized for low-light, outdoor, and high-traffic conditions, and integrate it into a Python service that processes RTSP streams, triggers alerts, and stores tagged video clips. I will also implement facial recognition with your watchlist and deliver a fully documented setup with validation results across all required scenarios. If you send the message, we can discuss the project more. Thanks.

@MZITSERVICES

Hi there, I am A.R.M. MASUD, with a strong background in Data Science. As a Python developer, I have extensive experience building robust, scalable, and efficient solutions that address various business needs. I understand the importance of delivering high-quality, well-architected code, and I am committed to working closely with you to ensure the success of this project. I implement core functionality using Python, utilizing relevant libraries and frameworks such as Pandas, NumPy, GUI, SciPy, Matplotlib, Seaborn, Plotly, Scikit-learn, TensorFlow, Keras, PyTorch, spaCy, Flask, Django, FastAPI, OpenCV, and Jupyter. I am a professional responsible for extracting actionable insights and knowledge from large volumes of data through Machine Learning models, including CNNs, RNNs, LSTMs, GANs, Transformers, FNNs, ANNs, and DNNs. I conduct comprehensive unit, integration, and performance testing to ensure the solution is error-free and optimized. https://www.freelancer.com/u/MZITSERVICES I appreciate the opportunity to submit this proposal and am excited about the possibility of working with you to bring your project to life. Thanks A.R.M MASUD

@ivank69

Hi there. Will the pipeline run person detection and face recognition as separate stages, so facial matching only triggers when frame quality passes a clear threshold? Do you already have labeled footage from your own cameras for night, outdoor, and high-traffic conditions, or should the first phase include validation and fine-tuning on a smaller custom dataset? This system should be built as a real-time vision service on your Nvidia GPU server - RTSP ingestion, person detection, event-based clip recording, webhook alerts, and optional face matching only when image quality is reliable enough. Worked on similar vision and automation systems before where the main challenge was not only detection accuracy, but keeping alerts fast and reducing false positives across poor lighting and busy scenes. Facial matching also had to be separated carefully from detection so low-quality frames did not create noisy results. Solved that by structuring the pipeline into stream ingestion, detection, event recording, and gated recognition stages, then validating performance by environment, which improved stability and made results easier to trust. Strong experience with Python, CUDA-enabled CV pipelines, YOLO/OpenCV-based systems, real-time processing, and production-style backend services, so this project is a strong match. Ready to start immediately and build a clean, testable detection service for your existing camera setup. Best, Ivan

@smstaci

Hi there, I’ve reviewed your project to enhance your security camera network with AI capabilities, and I can deliver a robust solution. With extensive experience in computer vision, TensorFlow, and PyTorch, I will fine-tune a model that accurately detects individuals in varied environments, including low-light and outdoor conditions. I will leverage your Nvidia GPU server for optimal performance. Deliverables will include the trained model files, a Python-based API to process RTSP streams and trigger alerts, and comprehensive setup instructions along with a validation report assessing performance across the specified conditions. I’m ready to start and ensure the system meets your accuracy and responsiveness targets. Thanks, Pavlo.

@johnedwardl

Hi, I will develop an AI-powered module for your security camera network that reliably detects people and responds in real time. My experience with TensorFlow and PyTorch, particularly in mixed-environment scenarios, makes me confident in delivering a robust solution that meets your criteria. The approach involves fine-tuning a computer vision model specifically for your unique conditions, ensuring accuracy in low-light, outdoor, and high-traffic settings. I’ll implement a system that triggers real-time alerts, records events, and integrates facial recognition seamlessly. Using your Nvidia GPU server, I’ll ensure efficient performance. To clarify, I will provide trained model files, a lightweight Python API for RTSP stream ingestion, and comprehensive setup instructions along with a validation report. My focus will be on achieving the accuracy and responsiveness you expect. Let's discuss the watch-list specifics and any additional requirements you might have. Thank you.

@sadam61

Hi there, I'm excited about your project to upgrade your security camera network with an AI-powered detection module. I have extensive experience with computer vision projects like this, particularly in training models using YOLO and TensorFlow, ensuring robust performance in diverse environments. My skills in Python will help develop a lightweight API to handle RTSP streams and integrate seamlessly with your alerting system. I can start immediately and am confident in delivering a system that meets your accuracy and responsiveness benchmarks. Let’s discuss any specifics you have in mind so we can ensure a perfect fit for your needs. Best regards, Sadam

@daxm0

Hi there, I’m excited about the opportunity to work on AI Surveillance Person Detection System and believe my skills and experience make me a strong fit for this project. I have a clear understanding of your main objectives. I’ve carefully reviewed the requirements to ensure nothing is overlooked. I will deliver a final result that aligns perfectly with your expectations. With my background as a Senior Software Engineer, I have strong expertise in C Programming, Python, Machine Learning (ML). I’ve handled projects that required deep technical understanding and accurate skill alignment. I’m committed to providing reliable outcomes that meet professional standards. Before we proceed, I’d like to clarify a few points. Please feel free to message me in the chat so we can go over them together. Talk soon, Dax Manning

@cindyviorinar

Hi there, I’ve read your AI surveillance brief and I’m confident I can deliver a robust person-detection module that runs on your CUDA-enabled Nvidia server. I have hands-on experience building secure, scalable APIs and structured backends in ASP.NET Core/C#, and I pair that with Python-based CV stacks (YOLO/PyTorch/OpenCV) for reliable detection pipelines. I will fine-tune a model for low-light, weather and high-traffic scenarios, implement RTSP ingestion, event recording with organized archive and tags, and an API endpoint to trigger your webhook and optional facial match checks against your watch-list. Next step: I’ll prepare a short validation plan and initial training pass, then share model artifacts and a lightweight service for your testing. Do you have example RTSP feeds and a labeled watch-list (format/size) I can use for initial fine-tuning and validation? Thanks, Cindy Viorina