Hire the Best Internet of Things Specialists
in the United States

I am a Materials Science Ph.D. and AI/ML consultant specializing in machine learning, industrial AI, materials informatics, chemistry-driven process optimization, and decision-support systems. I help technical teams turn messy experimental, operator, sensor, process, and production data into predictive models, dashboards, and AI workflows that support faster decisions, lower chemical usage, better process control, and measurable operational savings. I have worked directly with CTOs, process engineers, plant operators, project managers, and technical leadership to translate operational problems into deployable AI solutions. My focus is accelerating decision making. What I deliver: • Real-time prediction models for industrial and chemistry-driven processes • Decision-support AI tools for operators, engineers, and managers • Machine learning models for process optimization, quality control, and performance prediction • Transformation of operator logs and process records into clean, model-ready datasets • Exploratory data analysis to identify process drivers, anomalies, and failure patterns • Anomaly detection for sensor, production, experimental, and operator-recorded data • Time-series modeling for process monitoring, forecasting, and live decision support • Tree-based regression and classification models for interpretable industrial prediction • Hierarchical classification workflows for complex scientific and materials datasets • Deployment-ready dashboards and applications for technical users Relevant industrial AI experience: • Built predictive models for real-time process variables, including treatment performance, effluent quality, chemical response, and operational stability. • Developed decision-support workflows that helped operators evaluate process conditions and accelerate treatment decisions. • Converted inconsistent operator logs and process records into structured datasets for machine learning, dashboarding, and deployment. • Created models to support chemical dosing optimization, reducing unnecessary chemical use while maintaining target process outcomes. • Built classification and prediction workflows for complex materials, chemistry, and industrial datasets. • Developed exploratory analytics and anomaly-detection workflows to identify abnormal process behavior and data-quality issues. • Designed model-development pipelines covering data cleaning, feature engineering, model training, evaluation, interpretation, and deployment. • Delivered working applications and dashboards for stakeholders including engineers, managers, operators, and executive leadership. Core expertise: • Industrial AI and machine learning model development • Materials informatics and chemistry-driven process modeling • Exploratory data analysis and process-data diagnostics • Anomaly detection and outlier analysis • Time-series modeling and real-time prediction • Regression, classification, and hierarchical classification • Tree-based modeling, feature importance, and model interpretation • Decision-support dashboard and application development • Scientific data cleaning, visualization, and reporting • End-to-end project execution from raw data to deployed tool Selected project areas: Industrial Process Prediction and Decision-Support AI Developed industrial AI work includes developing machine learning models and operator-facing decision-support tools for real-time process prediction, chemical dosing support, treatment performance monitoring, and process optimization. I converted operator-recorded and real-time process data into structured datasets, predictive models, and user-facing applications that helped operators and engineers make faster treatment, dosing, and process-control decisions. These tools reduced decision time, supported live process monitoring, and identified potential operational savings of $100K–$200K per year through improved chemical use and process control. Materials Informatics and Scientific ML Built predictive models for materials-property estimation, chemistry-performance relationships, and scientific feature engineering. Work includes modeling alloy properties, chemistry-driven performance, and complex experimental datasets. Anomaly Detection and Process Diagnostics Created workflows to identify abnormal sensor behavior, inconsistent operator records, outlier samples, and unusual process conditions. These analyses helped improve data quality and model reliability before deployment. Why Work With Me? I combine deep scientific training with practical AI/ML development. My strength is translating complex technical data into models, dashboards, and decision-support tools that operators, engineers, and managers can use. I can help you move from raw, messy data to a working AI solution that supports better decisions, faster analysis, and measurable operational value.

I am a Senior Embedded Systems Engineer with strong experience in firmware development, PCB design, IoT systems, embedded Linux, robotics, industrial automation, and edge AI. I help clients turn ideas into reliable products by handling the full development process from architecture and component selection to schematic design, PCB layout, firmware, testing, debugging, and production ready documentation. My core expertise includes: - Embedded Firmware: C/C++, STM32, ESP32, nRF52, RP2040, FreeRTOS, Zephyr, bare metal firmware - PCB & Hardware Design: KiCad, Altium, schematic design, PCB layout, BOM, Gerbers, DFM, debugging - Embedded Linux: Yocto, Buildroot, device tree, Linux drivers, bootloaders, system integration - IoT & Wireless: BLE, Wi-Fi, LoRa, Zigbee, MQTT, TCP/IP, OTA updates - Industrial & Automotive: CAN, CAN-FD, RS-485, Modbus, J1939, UDS, PLC/SCADA integration - Robotics & Control: motor control, BLDC/FOC, sensor fusion, real time control, ROS 2 - Edge AI: TinyML, TensorFlow Lite Micro, Edge Impulse, computer vision, sensor based AI - Desktop Tools: Qt/C++, Python automation, serial/CAN tools, test software, firmware update utilities - FPGA Support: Verilog/VHDL basics, FPGA integration, high speed data acquisition support I can support projects such as: - Custom IoT devices - Sensor based embedded products - Wearable electronics - Industrial controllers - Robotics systems - Automotive CAN devices - BLE/Wi-Fi connected products - Embedded Linux gateways - PCB redesign and hardware debugging - Firmware rescue and prototype bringup I focus on building systems that are reliable, testable, manufacturable, and easy to maintain. Whether you need a prototype, firmware fix, PCB redesign, or complete embedded product development, I can help move your project from concept to working hardware. Thank you for visiting my profile. If you're looking for an experienced Embedded AI & IoT Engineer who can help turn ideas into reliable products, I'd be happy to discuss your project. I look forward to working with you.

I am a data engineer with extensive experience in automation, cloud, data pipeline, intelligence model, edge, mobile, and hardware IoT integration. I have particular expertise in sensor applications, smart cities, home automation, and telemetric IoT fleet management. Selected Technical Skills: Languages: Python, Typescript, SQL, node.js, C/C++, Java, Kotlin, Swift Data: Snowflake, DataBricks, Kinesis, Spark, PostgreSQL/PostGIS, MongoDB, Jupyter, R, QGIS Cloud: k8s, AWS, DigitalOcean, Terraform, Helm, Docker, RabbitMQ, SQS, Redis Edge: MQTT, LoRaWAN, EQMX Embedded: STM32, embedded Linux, Raspberry Pi, AVR, Modbus Physical: CAD, PCB design, 3D printing, ultrasound, chemistry

Hello! I'm Chris Renshaw, a Senior Mobile Developer with over 15 years of experience building native Android and iOS applications and a proven specialty in IoT and hardware integration that most mobile developers simply don't have. As Director of INDUS Innovation Labs and acting CTO of Neuroregenesis, I lead an international team of developers, designers, and contractors delivering end-to-end mobile solutions across healthcare, fitness, entertainment, and maritime industries. What sets me apart is my deep ability to bridge the gap between mobile apps and physical devices. I have built BLE communication libraries that powered a commercial fitness equipment line generating over $250 million in sales. I have architected health monitoring platforms integrated with Fitbit and medical sensors at UnitedHealth Group, directly contributing to what became a billion-dollar initiative. I have engineered real-time audio streaming solutions using Raspberry Pi and UDP protocols. I have led Android development for Carnival Cruise Line's shipboard systems, integrating facial recognition and document-scanning hardware across multiple applications. I don't just write code. I own the full mobile lifecycle from architecture to deployment, and I know how to lead teams that deliver. My technology stack includes Kotlin, Jetpack Compose, Swift, SwiftUI, Room, Hilt, BLE, MVVM, and deep experience with embedded device communication, offline-first design, and firmware integration. Whether you need a polished standalone app or a sophisticated mobile experience that communicates with your hardware, sensors, or wearables, I bring the technical depth and leadership to get it done right. Let's build something great together.

I help teams design and ship connected hardware products, whether you are building a new venture or expanding an existing product line. From high-level system architecture through schematic design, PCB layout, embedded firmware, cloud integration, and production readiness, I support the full product lifecycle. I specialize in commercial embedded and connected systems that must be reliable, scalable, and ready for real-world deployment from day one. With over six years of experience designing electronic products and the firmware that drives them, I work across hardware, embedded systems, and cloud infrastructure. My work includes custom electronics, production-ready PCB design, firmware architecture, and enclosure development for commercial products. Much of my background is in IoT environmental sensing and control systems, but my experience extends across embedded platforms and connected devices more broadly. I have five years of experience working within the AWS ecosystem, designing systems that leverage MQTT, AWS IoT Core, Lambda, ECS, RDS, and related services for secure data collection, fleet management, and operational reporting. I have extensive experience with Espressif’s ESP32 platform along with STM32 and other embedded systems, delivering products ranging from wireless sensing devices and lab equipment access control to industrial and autonomous systems. I frequently work on systems where reliability is critical. This includes products that must operate continuously in the field, integrate with safety-related infrastructure, or meet strict operational requirements. I design with long-term reliability, serviceability, and regulatory considerations in mind, including awareness of certification pathways such as FCC, CE, UL, and related compliance processes. In addition to system design, I maintain in-house rapid prototyping capabilities that allow hardware to move quickly from concept to tested prototype. This includes PCB prototyping, embedded firmware bring-up, and mechanical prototyping using both additive and subtractive fabrication methods with engineering-grade materials, along with small-batch electronics assembly and validation. These capabilities enable faster iteration cycles, early hardware validation, and smoother transitions into manufacturing. My focus is on building systems that are not only functional, but robust, maintainable, and ready for real-world deployment and production.

I build two things that rarely come from the same person: embedded hardware that ships, and AI systems that run real businesses. On the hardware side, I design end to end. Custom PCB in EasyEDA through JLCPCB manufacturing (BOM, Gerber, CPL), then the firmware that runs on it: ESP32 S3, C3 and C6, FreeRTOS dual core architecture, BLE, WiFi, MQTT, OTA updates, ultra low power design. Seven custom boards manufactured with full SMT assembly, 10K+ lines of production firmware, one patent filed with 226 claims on adaptive battery management with Edge AI, and a published research paper on wireless power infrastructure. On the AI side, I build agents that do real work, not demos. I currently run an autonomous business agent in production for a service business: it handles customer conversations on WhatsApp, books appointments through calendar integration, reads payment receipts with vision AI, and reconciles the money at the end of the day, with a human takeover bridge through Telegram. Multi tenant architecture, ready to onboard new businesses. I also build algorithmic trading systems with full ML data pipelines, where every strategy is validated against out of sample data before it touches a live account. What clients get from me: someone who understands the whole chain. The sensor, the board, the firmware, the radio, the backend, the AI layer, and the business result it has to produce. I flag risks early, I document everything, and I deliver with receipts, build footage and handover docs the client can actually use. Recent work: BLE triggered hardware prototype delivered ahead of schedule with same day milestone approval, and a LoRa ski tracking device on Heltec hardware