AI-Powered Security Camera & Sensor Alert System (Prototype/Pilot Build)

@webbookstudio

Hi there, We understand you're looking to develop a pilot AI security monitoring system to replace traditional on-site guarding, utilizing IP/CCTV cameras and motion/perimeter sensors to detect and alert for genuine events. Our team at Webbook Studio has relevant experience with computer vision (OpenCV, React Native) and IoT/camera integration, as seen in our music voting mobile app project using React Native and REST API. We propose a tech stack including IP cameras, a YOLO-based AI model for object detection, and a cloud-hosted dashboard for real-time alerts and live feed monitoring. Can you share more about your expected timeline for the pilot build and how you envision the system's scalability for multiple sites? Feel free to message us to discuss the details! — Webbook Studio

@diektech

Hi — Elias here from Miami. I see you're working on an AI-powered security monitoring system to enhance safety without traditional guards. The goal of replacing on-site security with an efficient, tech-driven solution is both ambitious and timely. The real technical challenge here often lies in ensuring reliable real-time alerts and robust data handling. What usually matters most is how well the system can scale with added cameras and sensors while maintaining performance. The tricky part is usually the integration of AI for accurate detection without overwhelming the user with false alerts. My approach would focus on building a modular architecture that allows for easy scaling and integration with various AI models. I’d prioritize maintainability and ensure that the system can evolve with future advancements in technology. I've developed similar systems where seamless integration and user experience were key, helping clients navigate complexities effectively. A few questions to better understand the scope: Q1 – What specific types of sensors and cameras are you planning to integrate? Q2 – How do you envision the user roles and permissions for accessing alerts and data? Q3 – Are there particular AI capabilities you want prioritized for this pilot? Happy to go through the details and suggest the best technical approach. Looking forward to hearing from you.

@installerpoint

Hello, Your pilot is a strong fit for a practical computer-vision monitoring prototype. I can structure the build around IP camera and sensor integration, person/vehicle/animal detection, event filtering, and remote alerts with a simple live-view dashboard. I would recommend validating an edge-versus-cloud setup early to balance reliability, connectivity, privacy, and operating cost, then deliver the work in the requested phases with clear pilot acceptance criteria. I understand that dependable real-world alerting matters more than unnecessary features, and I will keep the architecture scalable for additional sites. Check out my portfolio here:- https://www.freelancer.com/u/installerpoint Best Regards, Muhammad Adeel

@softsolution2000

I am a skilled developer with experience in computer vision and AI technologies such as OpenCV and YOLO. For the AI-Powered Security Camera & Sensor Alert System project, I propose to integrate IP/CCTV cameras and motion sensors, develop an AI detection layer for person/vehicle/animal classification, and create a real-time alerting system with a user-friendly dashboard. My recommended tech stack includes using reliable IP cameras, implementing a deep learning model for accurate classification, and hosting the system on a secure cloud platform. I will ensure seamless camera/sensor integration, accurate AI detection, and efficient alerting methods for real-time notifications. I have a track record of working with non-technical clients and explaining complex concepts in a clear and understandable manner. My focus is on delivering a working and reliable system that meets your specific needs, without unnecessary complexity or over-engineering. I look forward to the opportunity to collaborate with your team on this exciting project and help you transition to AI-led security monitoring. See the above links please.

@AwaisChaudhry

Hello, Your pilot needs dependable event verification rather than simple motion alarms. I can help shape a practical web-based monitoring prototype with a responsive dashboard for live camera views, alert history, site status, and future multi-site expansion. I would recommend a phased architecture: camera and sensor streams feeding a secure AWS backend, with a computer-vision service handling person, vehicle, and animal events. The dashboard can be built in HTML with a clear UI / User Interface, while AI Content Creation can support structured event summaries and operator-friendly alert descriptions. Alerts can be routed through SMS, WhatsApp, or Telegram according to reliability and operating cost. For the pilot, I would prioritize authenticated access, camera connectivity, event timestamps, snapshots or clips, configurable after-hours rules, and an audit trail. This keeps the first deployment focused while leaving room to improve model accuracy and add sites later. I can also document the trade-offs between edge processing, cloud inference, bandwidth, latency, and ongoing costs for your UK team. Which camera protocols, sensor types, and alert channels are already available at the pilot site, and what response time is required for verified events? I’ll work in clear phases and communicate the technical decisions in plain English, with reliability tested against real site conditions. Regards, Muhammad Awais

@nikhilgarg96

Hi Being an AI-first development company, we are well-versed in leveraging computer vision and IoT technologies to create intelligent systems, making us the ideal candidate for your AI-powered security camera project. Our proficiency in OpenCV and other similar technologies will enable us to connect your IP/CCTV cameras and sensors seamlessly. We understand the importance of differentiating between people, vehicles, and animals to reduce false alarms, and thus we can leverage our expertise in AI and computer vision models like YOLO to increase accuracy significantly. Real-time alerts with simple remote access are fundamental to the success of any security monitoring system, and we can guarantee their provision at every level. We will thoroughly handle camera integration with live-feed while ensuring a robust AI detection layer for precise classification. Moreover, our experience with crafting intuitive dashboards will help you effortlessly manage feeds and track recent alerts from anywhere. Cost-efficiency coupled with real-world reliability is key when transitioning from traditional security measures, and these principles have always guided our work. Thanks.....

@AneesaIBA

Good Day, I have read and understood the project details and understand you need a practical pilot AI security monitoring system that can identify genuine events from CCTV and sensors while reducing false alarms from simple motion detection. I can build the pilot around IP cameras with RTSP/ONVIF support, using a computer-vision model such as YOLO with OpenCV for person, vehicle and animal classification. For the backend, I’d recommend Python/FastAPI with a lightweight dashboard, with edge or cloud processing selected based on the site’s bandwidth, camera count and privacy requirements. I’ll structure the system in two phases: first, camera/sensor integration with live feeds and reliable AI detection; second, real-time alerts plus a simple dashboard showing camera feeds, detection events and recent alerts. Alerts can be connected through Telegram/WhatsApp/SMS depending on your preferred cost and reliability trade-off. The pilot will be designed with future multi-site expansion in mind without over-engineering the first deployment. I’ll also document the recommended camera hardware, AI approach, hosting and alerting architecture so the trade-offs are clear. Could you please share the expected number of cameras for the pilot site and whether the existing cameras support RTSP/ONVIF? Let’s build a reliable pilot first, prove the detection and alerting workflow, then scale it confidently across additional sites. Regards, Rabia Shaikh.

@ajharul

Hi, I can build your pilot AI-powered security camera and sensor alert system for your depots, yards, and rural land. This pilot will integrate IP/CCTV cameras and sensors, implement AI detection for people, vehicles, and animals, and provide a dashboard with real-time alerts via app, SMS, or messaging platforms. I bring 7+ years of web development experience to this project. To move forward, could we discuss your specific hardware and communication preferences to align the architecture with your scaling requirements?

@anirudhat

The architecture decision that decides whether this pilot scales is where inference runs. Streaming RTSP continuously to a cloud GPU sounds simplest but breaks on exactly the sites you're describing — rural yards on 4G with data caps, and a bandwidth bill that multiplies with every camera. I'd run detection on a small box at each site (a Jetson Orin Nano, or an N100 mini-PC with OpenVINO for lower cost) and send only event clips and thumbnails upstream. Sites stay independent, so one dropping off 4G doesn't affect the others, and adding site two is deploying another identical box rather than re-architecting. On compute, I wouldn't run the model on every frame: let the camera's own motion detection trigger, then run YOLO on those frames to classify. Same accuracy, a fraction of the hardware. For the model itself, YOLOv8 or v11 at small size already classifies person, car, truck, dog and similar out of the box, so no training is needed for a pilot. What I'd build instead is a feedback loop — every alert your team marks as false becomes labelled data, so the system gets measurably better on your actual sites rather than on a benchmark. On false alarms, I'd set expectations honestly: class detection alone won't solve them. In the field the real culprits are insects and spiders on the lens at night (IR illuminators attract them), moving vegetation, rain in IR, and headlights sweeping a fence line. What actually fixes those is object tracking across frames — requiring the same tracked object to persist for several frames before alerting — plus minimum object size, defined detection zones and line-crossing rather than whole-frame motion, and time-of-day rules. That tuning work is where a pilot succeeds or fails, more than the model choice. Reliability features I'd consider non-negotiable: camera heartbeat monitoring, so a camera going offline raises its own alert (that's the first thing an intruder causes), a watchdog restarting the pipeline automatically, and local buffering so events aren't lost when mobile data drops. For alerting, Telegram's bot API is free, instant and ideal for a pilot; WhatsApp needs a Business API provider and pre-approved templates, which adds cost and delay, so I'd suggest starting with Telegram plus SMS fallback and revisiting WhatsApp once the detection layer is proven. Every alert carries a snapshot and short clip so your operator can judge in two seconds without opening anything. Dashboard would be a web app with live view over WebRTC via MediaMTX rather than HLS — HLS adds 10 to 30 seconds of delay, which is useless when someone's checking a live incident. One thing worth raising early given you're coming from manned guarding: monitored CCTV in the UK brings a DPIA, signage, retention policy and ICO code obligations, and the SIA position differs depending on whether you're monitoring public space. You'll know that landscape better than me, but the system should be built to support it — configurable retention, audit logs of who viewed what — rather than retrofitted later. Phases as you set out, priced in small milestones so you only pay as each piece works: camera and sensor integration with live feed, then the detection and tuning layer, then alerting and dashboard. Tell me what cameras are on the pilot site and whether there's mains power and decent 4G, and I can start immediately on the edge pipeline.

@WebTechDesignBG

Hello, I see you’re looking to develop an AI-powered security system that effectively replaces traditional on-site guarding. This involves connecting IP/CCTV cameras and sensors, using AI to accurately differentiate between people, vehicles, and animals, and providing real-time alerts for genuine events. My approach would focus on a practical implementation that balances reliability with functionality, ensuring you have a system that works seamlessly across multiple sites as you scale. With 7+ years of experience in computer vision and IoT integrations, I can guide you through the process, helping to choose the right hardware and AI models while keeping things straightforward. I’ll break the project into clear phases: camera/sensor integration, AI detection, and alerting/dashboard setup. Here's a link to my portfolio for your review: https://pixoriq.com. What specific types of sites do you anticipate needing this system for, and do you have preferences for the cameras or sensors? Best regards, Ivan Mandinski

@corpmember29

Hello, AI SECURITY MONITORING & COMPUTER VISION DEVELOPER {{{ I HAVE WORKED ON SIMILAR AI CCTV MONITORING, YOLO, COMPUTER VISION AND REAL-TIME ALERT SYSTEMS BEFORE AND I CAN SHOW YOU RELEVANT WORK. }}} I went through your requirements and understand that you need a reliable pilot system that connects IP cameras and sensors, identifies people, vehicles and animals, reduces false alarms, and provides real-time remote monitoring. I have 11+ years of experience in software development, including Python, OpenCV, YOLO, computer vision, IP camera/RTSP integration, IoT, real-time event processing and cloud systems. For the pilot, I would recommend RTSP/ONVIF-compatible cameras, an edge device for AI inference using a YOLO-based model, Python/OpenCV for processing, and a lightweight cloud backend/dashboard. Alerts can be delivered through Telegram/WhatsApp/SMS depending on your preferred cost and reliability requirements. I will structure the system in two practical phases: Phase 1 for camera/sensor integration, live feeds and person/vehicle/animal detection; Phase 2 for alerting, event history and the remote dashboard. The design will remain simple for the pilot while keeping the architecture ready for multiple sites later. I WILL PROVIDE 2 YEARS OF FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE. I am available to start quickly and can work consistently with your UK team, explaining the accuracy, hardware and running-cost trade-offs clearly. Thanks, Christina

@seefattechnologi

Good Day!!====>>>>>>>>I can build the pilot AI security monitoring system with real-time person, vehicle and animal detection using CCTV/IP cameras, sensors and computer vision. With 10 years of experience in AI, Python, computer vision and full-stack development, I can use YOLO/OpenCV with RTSP cameras, event-based detection, cloud/edge processing, Telegram/WhatsApp alerts and a simple remote dashboard. I’ll prioritize reliable detection and low false alarms before scaling. Skills: Python, AI, Computer Vision, YOLO, OpenCV, CCTV/IP Cameras, RTSP, IoT, Telegram API, WhatsApp, Dashboard Development, Cloud Thanks!! Parminder

@sagarjain4010

Hi, Your pilot needs to turn CCTV + sensor activity into trusted security events—not constant motion alerts—so your team can know when a person, vehicle, or animal actually requires attention. I can build: • IP/RTSP camera & sensor integration • Person/vehicle/animal detection • Event filtering to reduce false alarms • Real-time Telegram/WhatsApp/SMS alerts • Remote live-view & recent-alert dashboard • Event history and configurable rules • Pilot architecture ready for multiple sites For the pilot, I’d recommend validating an edge-vs-cloud setup first, balancing detection accuracy, connectivity, hardware cost, privacy, and ongoing running costs. Please note: The budget and timeline in my bid are placeholders. How many cameras and sensors will the pilot site use, and do you already have existing IP cameras? Share those details and I can recommend the most practical setup and phase the build accordingly. Best regards, Sagar

@C0RETECHIES

Hello, System understanding: The system will ingest live streams from IP/CCTV cameras and motion/perimeter sensor events, run AI classification to distinguish people, vehicles, and animals, suppress false alarms, and push real-time alerts via app/SMS/WhatsApp/Telegram while providing a remote dashboard for live view and alert history. Technical approach: Use RTSP/MQTT for camera streams, OpenCV with YOLOv8 (or TensorFlow Lite) for on‑edge or server‑side detection, Node.js/Python backend to fuse sensor data, Twilio/WhatsApp API and Telegram bot for alerts, React frontend with WebSocket for live feeds and alert list, PostgreSQL for event storage, deployable on AWS EC2 or Docker for easy scaling. Core modules: Camera ingestion & sensor fusion, AI detection engine (person/vehicle/animal), Alert dispatcher (SMS/WhatsApp/Telegram/ push), User dashboard (live view, alert timeline, site config), Scaling & config management (multi‑site ready). Relevant systems: SecureCom (end‑to‑end encrypted communication) demonstrates our security‑focused engineering; CoreWipe (GrapheneOS security app) shows experience hardening devices and handling sensitive data streams. Implementation strategy: Phase 1 - Camera/sensor integration + live feed (≈10 days); Phase 2 - AI detection layer (≈10 days); Phase 3 - Alerting, dashboard, testing & pilot rollout (≈10 days). Iterate with feedback after each phase. Questions: 1. Which camera brands/models or RTSP endpoints do you plan to use, or should we recommend specific hardware? 2. What is the expected alert volume per site per day to size the notification channels? 3. Do you have a preference for alert delivery (SMS only, WhatsApp, Telegram, or app push) and any existing dashboard UI we should align with?

@Microlent

Hello, I am Dr. Rajesh Rolen, PhD in Computer Science & Engineering, with experience of over 20+ years in Web Design, Web Development, Website Design, UI / User Interface, HTML As a preferred freelancer in the top 1%, I have done 400+ projects here on freelancer.com, I have 4.9 ratings out of 5 on average, which showcases my quality of work and timely delivery. Key Highlights: - Free Hosting Support on the Cloud or any desired platform. - Free 3 months of post-delivery support to ensure that our client doesn’t face any challenges after the launch of the project. - Free Dedicated tester on projects to ensure quality delivery, so clients don’t need to act as a tester. - 10+ Years experience UI/UX team to ensure intuitive UI. Portfolio: https://www.freelancer.com/u/Microlent Please open the chat and send me a message, so we can have a more detailed discussion about the project to give you the project timeline and cost. Thank you for considering my services. I look forward to engaging in a productive conversation and understanding how I can be of assistance in bringing your project to life. Regards Rajesh Rolen

@marjanahmed13

Hi! My name is Marjan and I'm here to offer you my services as a skilled applicant with over a decade of experience working on Freelancer.com. I believe I am the best fit candidate for this project due to my extensive experience; I would like to have a discussion to get to know that we both are on the same page. Once the scope will be locked, I will start working on it right away.

@AnumFatima210

Hi, I went through your project details and understand what you're looking to achieve. I'd be interested in working with you on this. Based on the requirements you've shared, I can handle the project from start to completion while keeping the work aligned with your expectations, timeline, and desired outcome. My approach is straightforward: first, I'll make sure the requirements and expected deliverables are clear. Then I'll complete the work in structured stages, share progress along the way, incorporate your feedback, and deliver the final work after everything has been reviewed. Before we begin, I have a couple of questions about your requirements that will help me understand the scope more accurately. Feel free to message me so we can discuss the details and determine the best way to move forward. Best regards, Anum

@crtvecode

You're looking to build a reliable AI security monitoring system that connects to those IP/CCTV cameras and uses computer vision to distinguish between people, vehicles, and animals. This is a common challenge, especially when it comes to reducing false alarms, I can help you set up the camera integration and live feed, implement the AI detection layer with OpenCV and YOLO, and create a simple dashboard for alerts. And I can complete the work first so you can test everything before making any payment. You'll only award the project once you're satisfied with the results, my bid is 329 USD, broken down into phases: camera/sensor integration, AI detection, and alerting/dashboard setup. I'm ready to start right away, let's get this pilot up and running! Rajavel - Expert in AI, computer vision, and IoT integration.

@HadiDar786

Hi, I've reviewed your project "AI-Powered Security Camera & Sensor Alert System (Prototype/Pilot Build)" and I have hands-on experience across Ai Content Creation, and UI -- exactly the mix this project needs. I can handle the full build end-to-end, keep the code clean and well-structured, and update you regularly as I go. Happy to discuss the specifics and get started.