Internet of Things 2018-05-14T15:40:09+00:00

Internet of Things Services

A consulting led approach to providing IOT solutions.

Internet of things Services

Canspirit’s comprehensive end-to-end IOT solution provides an agile and scalable approach to robotic process automation. Typical benefits delivered by our IOT offering include:

  • Implement industrial automation solutions empowered by the Internet of Things
  • Implement industrial automation solutions empowered by the Internet of Things
  • Step by Step approach towards Industrial Automation

5- STEPS for IOT and Industrial IOT

Canspirit offers a quick start 5- STEP program for IOT Automation – Assesment‚ Hardware and Connections, IOT Platform, Predictive Analytics and Realtime Analytics.

5-Step IOT Approach

Canspirit’s 5 Step IOT  Approach

IIOT Industrial Automation : Quick Start – 5 Step Program

Canspirit offers a 5-Step program designed to quickly bring your organization up to speed on the range of IOT and Industrial Automation solutions, so that you can identify the tools best suited to meet your business needs, and devise a plan to get you up and running fast.
Canspirit believes that with the industrial automation solutions empowered by the Internet of Things, manufacturing production facilities and products themselves can be outfitted with computing hardware and connected using standard networking means. This allows separate parts of a production line communicate with each other in near real time and makes the entire manufacturing process much easier to monitor and control.
During the program we’ll work with you to:

  • Understand your Automation objectives.
  • Understand your level of familiarity with IOT technologies.
  • Explore potential Automation solutions and products that leverage your business’s existing assets.
  • Prioritize your Automation solutions into a roadmap, based on value to your business, technical risk, and duration.
  • Document your  Business Automation strategy.

Industrial IOT : Quick Start – 5 Step Program

IOT Business Goals- Assessment : Step 1

The success of an IoT solution is squarely dependent on the clarity of problem statement.

  • The stakeholders of an organization should identify the expected outcome along with the key success metrics.
  • They should precisely know how the solution will impact the productivity, efficiency, and customer satisfaction in the long run.
  • They should precisely know how the solution will impact the productivity, efficiency, and customer satisfaction in the long run.

Hardware and Connected solutions: Step 2

Identify the hardware and devices participating in the connected solution
Enterprise IoT solution has to diligently identify the hardware, equipment, and machinery from an existing inventory of devices. Based on the business goals and expected outcome, it may have to partner with an OEM to source appropriate sensors, actuators, adapters, bridges, and other hardware. The combination of existing devices and the identified components from the devices layer, which becomes the source of the comprehensive data acquired by the platform.

An enterprise IoT solution deals with a variety of connectivity mechanisms and protocols.
It includes how the sensors and actuators talk to legacy devices, the raw format of the datasets generated by the devices, how the devices talk to the edge layer, the protocol translation that takes place between the devices and the gateway.
Legacy devices use PLCs, RTUs, and telemetry systems that are based on BACnet and Modbus to generate data.
Sensors talk to the gateway and edge layer through Bluetooth Low Energy, Z-Wave, ZigBee, WiFi, Ethernet, Serial Port. The data format can be CSV to XML to JSON. The edge layer will have to translate the transport protocol and wire-format protocols before sending the data to the IoT platform.
By the end of this step, the organization would have identified everything that it takes to onboard physical devices to the connected platform.

Selection of an IOT Platform: Step 3

An IoT platform which serves as a control hub for such connected production facilities. On the application and data processing levels, the platform should offer a rich feature set for cloud enablement and generic data treatment, which can be used to rapidly assemble end-to-end IoT applications for industrial systems automation, predictive maintenance, and remote monitoring.
Our Platform should be hardware Agnostic so that it can be easily integrated with a broad variety of sensors, controllers, machines, and device gateways, enabling many-to-many interoperability between them.
Through this interoperability and unified data sharing, separate parts of the production line become more responsive and capable to instantly react to different events or change their configuration settings accordingly.
Failure prediction and troubleshooting also become reliable and straightforward.
Also like any other enterprise solution, security is critical for IoT projects. Datasets must be carefully anonymized, encrypted, and compressed before processing. A comprehensive governance model is necessary to restrict access to sensitive data and reports. Policies will define which roles and personas are allowed to control the devices, and accessing the business intelligence dashboards. IoT security is tightly integrated with existing corporate policies and security best practices.
This phase of planning will also include identification and implementation of complex business rules that define various policies for connecting to the devices and accessing the data.

Factor in machine learning and predictive analytics: Step 4

The real value of IoT is realized through actionable insights based on intelligent algorithms.
While not every implementation may need machine learning and predictive analytics, the chances are that it may become a critical requirement in the future.
When defining the data pipeline for processing the sensor data, architects should leave enough room for extensibility.
By factoring this feature, it will become easy to add predictive analytics to an IoT solution at a later point.

Near Real-time Analytics: Week 5

As discussed earlier, individual data points need to be monitored and analyzed as they are generated. For example, it may be too late before the IoT platform shuts down an LPG refilling machine after detecting an unusual combination of pressure and temperature thresholds. Instead, the anomaly should be detected within milliseconds followed by an immediate action triggered by a rule. The other scenario that demands near real-time processing is healthcare. Vital statistics of the patients are monitored in real time.
As data enters the IoT platform, an ingestion layer will route a subset of that through a pipeline that is designed to deal with the real-time data points. That pipeline is often called as the hot path analytics. Enterprise architects need to identify the metrics that take the hot path analytics.

IOT Automation Expertise

Canspirit has implementation  and expertise with range of IOT products

Canspirit IOT expertise Canspirit IOT expertise