IoT Gateways are emerging as an essential component in building a robust IoT solution. Nowadays, OEMs are more focused on developing next-generation IoT-connected solutions having much higher analytical capabilities, and so the demand for IoT Gateway is increasing rapidly. But when we talk about developing IoT solutions, OEMs face multiple challenges such as time, compatibility, scalability, security, privacy concerns, etc., and to avoid these challenges OEMs look for a ready-to-use IoT platform, which can customize and save time and their development cost.
VOLANSYS CENTAURI 200 and IoTify are proficient enough to overcome the above challenges and meet the requirements of different industries. IoTify with CENTAURI 200 platform is a flexible, secure, and feature-rich multi-platform IoT cloud & mobile app framework to create IoT solutions with AI/ML capabilities. It enables the OEMs, automotive industries, businesses to achieve key goals, obtain actionable insights, drive critical decisions, relieve from repetitive tasks, and create exciting, new, and innovative products and services.
Readiness of CENTAURI 200 & IoTify Platform for Application Development
CENTAURI 200 platform targets one of the widely used application areas such as anomaly detection with the supported BLE/RS-485/RS-232/CAN sensors for AI/ML use cases in the platform architecture.
The CENTAURI 200 Software framework is developed with AWS IoT Core SDK, AWS Kinesis SDK, and Tensor Flow Lite Framework for the anomaly detection whereas on the other side cloud uses AWS services developed with AWS serverless architecture having SageMaker, Kinesis, S3, Lambda, IoT Core, AWS Route53, CloudFront, Cognito, API Gateway, CloudWatch, SNS, DynamoDB, EMR, IAM services.
The focus of the cloud platform is to gather data, train model, auto-deploy model, and send notifications to the gateway for the newly developed model. For anomaly events, the cloud sends the push notification to the IoTify mobile user.
Fig- 1: High-Level Platform Architecture
CENTAURI 200 is developed with a data collector service for each type of protocol that fetches the sensor data from the sensors and sends it to the sensor data streamed to the cloud via AWS Kinesis stream. However, OEM dashboard allows users to create history and an AI/ML configuration for a list of devices of the same type with sample frequency. It supports model deployment (auto/manual), auto train model, model retraining with multiple other features. The model training is performed using Sagemaker with the historical data received on the Kinesis stream according to the predefined reporting frequency. The model once trained is deployed on the CENTAURI 200 for future anomaly detection.
CENTAURI 200 runs the inference manager service on the gateway once the model is deployed for the configured particular end device. The model is loaded and the live data of the sensors are fed to the model. The anomaly detection is sent as an MQTT message to the cloud. The cloud agent service running on the gateway supports sensor registration, fetch AI/ML/ historical data over MQTT, download/update the model received from the cloud, etc.
Based on the historical data of the particular configured sensor in the gateway, the IoTify Cloud registered OEM user and mobile app user will be able to see the graphs with monthly, weekly and daily data for analysis. The graph also provides the average data of the anomaly detection registered for the sensor. This enables the OEM user to take proactive measures and decisions for their machinery or other industries.
To understand the above scenario, let’s take an example: Drilling and extraction are key processes associated with the Oil & Gas industry. The industry meets the specific requirement of extraction and production activities using various autonomous equipment. Using AI/ML is identified as the best solution for not only reading and recording the values from the available instruments, but also for analysing any sort of inconsistencies/anomalies. This helps increase the automation of key tasks and reduce the manual work. Preventive maintenance is planned periodically for specific tasks to keep equipment in good working condition. AI/ML enables preventive maintenance by helping the maintenance team take the precautionary steps in a proactive manner, thereby reducing equipment failure and ensuring safety of workers.
In addition to the above-mentioned contributions, there are numerous use cases where VOLANSYS – CENTAURI 200 IoT Gateway and IoTify – IoT Cloud framework with App and Gateway solution has performed tremendously and act as a single-stop solution. Let’s understand how the platform works in various industries:
Manufacturing Industry Applications
Manufacturing industries use various types of equipment and machinery on a regular basis for the production of consumer goods, automotive goods, etc. In such industries, asset management is required to increase the productive uptime, optimize the quality, and reduce operational costs while ensuring safety and timely delivery. To help achieve the goals, introducing AI/ML is targeted as a very practical and convenient solution. Here, sensors can be connected to mechanical devices as small as valves and as big as equipment such as generators, pumps, compressors, electric motors, boilers, etc. These sensors can read the data from the equipment and send it to the gateway which in turn will send it to the cloud. The data gathered from the equipment can be used to train the model and deploy it on the gateway at a regular interval for anomaly detection.
Advantages: Monitor/track assets smarter, resolve issues before they occur, maximize asset utilization, manage aging assets and infrastructure, elevate maintenance management, efficient utilization of power and energy.
Medical/Healthcare Industry Applications
BLE devices like Smartwatches and other wirelessly connected devices like oximeters, blood glucose monitors, etc enable constant tracking of the health of patients. Continuous data collected from the patients help the physicians to act proactively and identify the best treatment for the patients. These devices are connected with the gateway to identify the anomaly detection according to the model trained through the AI/ML framework to identify/detect any critical situations for the patients.
Advantages: Improved treatment, cost- reduction by cutting down visits to the hospitals, faster disease diagnosis, drugs and equipment management, etc
How OEMs are benefiting using AI/ML-enabled VOLANSYS Platforms – CENTAURI 200 & IoTify
- Upfront cost-saving up to 60% by using ready-to-market solution avoiding huge upfront costs
- High-value delivery to end customers by reducing downtime using AI/ML capabilities with help of predictive analytics for maintenance
- Exploring new revenue opportunities in the remote monitoring and service areas with the help of data available on remote management capabilities
- OEM can achieve a technological edge over competitors
- Better understanding of consumer consumption patterns for better business strategies
Thus, IoT platforms with the latest AI/ML capability is one of the major advantages which VOLANSYS deliver with their solution. We help in developing intelligent solutions for different industries using CENTAURI 200 & IoTify AI/ML framework support on Cloud and Gateway. Train your model using sensor data on Cloud and deploy the trained model on Gateway to detect an anomaly on the sensor data and inform the cloud for necessary action. The model training has adoptive learning capabilities using sensor data for accurate results.
Story 1: Developing and AI/ML-Driven Preventive Maintenance and Failure Detection System
Story 2: Integration of Smart Secure Digital Identity Solution with CENTAURI 200 and IoTify Platform
Story 3: Multiprotocol supported Health Monitoring Solution Integrated with CENTAURI 200 Gateway
About the Author: Neha Pande
Neha Pande is associated with VOLANSYS as a Principal Engineer for more than 1 year in the Product Development activities. She has experience of 8 years in Embedded testing with different domains.