The Internet of Things is transforming every industry — manufacturing, logistics, agriculture, healthcare, energy, and smart cities. Connected devices generate streams of data that, when properly captured and analysed, enable better decisions, predictive maintenance, automated operations, and entirely new business models.
At Nimaisoft, we have hands-on experience across the full IoT stack — from writing firmware for microcontrollers to building cloud data pipelines and edge AI inference systems. We help you move from isolated devices to a connected, intelligent operation.
Before building, it is essential to design the right system. A poorly designed IoT architecture leads to security vulnerabilities, scalability problems, expensive rework, and device management nightmares at scale. Getting the architecture right upfront saves significant time and money.
We help you define the full IoT architecture — device hardware selection, connectivity protocol choices, edge computing strategy, cloud platform selection, data storage design, and security model. We also develop proof of concept prototypes to validate assumptions before committing to full-scale development.
Our consulting covers:
Firmware is the software that runs directly on hardware — it controls how a device starts up, manages its sensors and actuators, handles communication, manages power, and responds to the environment. Writing good firmware requires a rare combination of hardware knowledge and software discipline.
Our embedded engineers write lean, reliable firmware for microcontrollers and microprocessors across architectures including ARM Cortex-M, RISC-V, and ESP32. We work in C and C++, follow industry coding standards, and implement rigorous testing processes to ensure firmware is stable in demanding real-world conditions.
What we develop:
A Board Support Package is the layer of software that adapts an operating system or firmware framework to a specific hardware platform. Without a proper BSP, the OS does not know how to communicate with your hardware — its peripherals, memory, clocks, and interfaces.
We develop complete BSPs for custom hardware boards, including kernel bring-up, peripheral driver integration, bootloader configuration, and hardware abstraction layers. We work with Linux BSPs for higher-capability devices and with lightweight RTOS BSPs for simpler embedded systems.
Device drivers are software components that allow the operating system to communicate with hardware peripherals — sensors, actuators, displays, communication modules, and storage. Writing correct, efficient drivers is critical for system stability and performance.
We develop custom device drivers for Linux and RTOS environments, implement hardware abstraction layers (HAL) that isolate application code from hardware specifics, and write integration tests that validate driver behaviour across operating conditions.
Processing AI inference in the cloud introduces latency, consumes bandwidth, and creates privacy concerns. Edge AI solves this by running machine learning models directly on the device — enabling real-time decisions without needing an internet connection.
We optimise and deploy ML models for edge hardware using TensorFlow Lite, ONNX Runtime, and Edge Impulse. We handle model quantisation and pruning to reduce model size for memory-constrained devices, implement hardware acceleration for devices with dedicated AI processors, and design the inference pipeline for efficient real-time operation.
Edge AI applications:
Choosing the right connectivity technology for an IoT deployment depends on range, power budget, bandwidth requirements, and environment. The wrong choice leads to unreliable connections, high data costs, or devices that drain batteries in days.
We have experience implementing all major IoT connectivity standards and selecting the right protocol for each use case.
Protocols and technologies we work with:
IoT platforms manage device connectivity, device lifecycle, data ingestion, and command delivery at scale. Choosing and correctly configuring the right platform is critical for a scalable, manageable IoT deployment.
We implement and integrate with all major IoT platforms — AWS IoT Core, Azure IoT Hub, Google Cloud IoT, and PTC ThingWorx for industrial scenarios. We set up device provisioning, certificate-based authentication, device shadow management, and bi-directional command channels.
Industry 4.0 is the fourth industrial revolution — the integration of digital technologies including IoT, AI, robotics, and cloud computing into manufacturing and industrial operations. IIoT (Industrial IoT) is the application of IoT specifically to industrial environments.
We build IIoT solutions for manufacturing plants, energy facilities, logistics warehouses, and port operations. Our systems connect PLCs, SCADA systems, and industrial machinery to cloud platforms, enabling real-time production monitoring, predictive maintenance, energy optimisation, and digital twin implementations.
Raw sensor data has little value on its own. The value comes from processing it — filtering noise, detecting patterns, triggering alerts, and feeding clean data to analytics systems and AI models. This processing can happen at the edge, in a gateway, or in the cloud depending on latency and bandwidth requirements.
We design and implement real-time data pipelines using Apache Kafka, Apache Flink, Node-RED, and cloud-native streaming services. We implement edge analytics on gateway devices for latency-sensitive decisions and build cloud-side processing for trend analysis, reporting, and model training.
Human-Machine Interfaces (HMIs) are the screens and controls that operators use to monitor and control industrial systems and IoT deployments. A well-designed HMI makes complex systems understandable at a glance and allows operators to respond quickly to alerts and anomalies.
We develop both embedded HMIs running on dedicated display hardware and web-based operator dashboards accessible from any device. We use Qt for embedded displays and modern web technologies (React, Grafana) for browser-based control interfaces.
Before committing budget to a full IoT deployment, it is essential to validate that the concept works in your specific environment with your specific hardware. Many IoT projects fail because assumptions about connectivity, sensor accuracy, or data quality were not validated early.
We offer rapid PoC engagements — typically 4–8 weeks — that build a working prototype, validate key technical assumptions, and produce a clear recommendation for the full-scale implementation. This de-risks your investment significantly.
Robotics is the next frontier for IoT intelligence — combining sensing, computation, and actuation to create systems that can physically interact with the world. This includes industrial robots, autonomous mobile robots (AMR) for warehouse logistics, agricultural robots, inspection drones, and humanoid robots.
We work with Robot Operating System 2 (ROS 2), the open-source framework that has become the standard for robotics software development. We build perception systems, motion planning algorithms, sensor fusion pipelines, and human-robot collaboration interfaces for industrial and commercial applications.