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. Internet of things offers many benefits such as :

  • Implement industrial automation solutions empowered by the Internet of Things
  • Enabling the smart usage of data using cutting edge technology.

  • 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, Internet of Things Platform, Predictive Analytics and Realtime Analytics.

5-Step IOT Approach

Canspirit’s 5 Step IOT  Approach

IOT Industrial Automation : Quick Start – 5 Step Program

Canspirit offers a 5-Step program designed to speed up your organization  on the range of IoT and Industrial Automation solutions. This helps in identifying the tools for  your business needs and in addition to plan accordingly with pace.
IoT empowers  the industrial automation solutions that outfits the manufacturing production facilities and products with computing hardware with the help of standard networking.  In other words this allows separate parts of a production line  to communicate with each other. Similarly it also  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

Identifying the hardware and device participating in connecting solution. Enterprise IoT solution has to identify the hardware, equipment, and machinery from an existing inventory of devices. It has to partner with an OEM to source appropriate sensors, actuators, adapters, bridges, and other hardware. The combination of existing devices provide the source of data which is 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, how the device generates the raw format of the datasets. It also includes how the devices talk to the edge layer. And above all, the protocol translation that takes place between the devices and the gateway.
Legacy devices use PLCs, RTUs, and telemetry systems that depends on BACnet and Modbus for generation of 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. After that, the edge layer translate the transport protocol and wire-format protocols before sending the data to the IoT platform.
The organization identifies everything that’s required to onboard physical devices for connecting platform by the end of this step.

Selection of an Internet of Things Platform: Step 3

An IoT platform serves as a control hub for  production facilities. The platform  offer a rich feature set for cloud enablement and generic data treatment on the application and above all provides data processing levels. This helps in assembling end-to-end IoT applications for industrial systems automation, predictive maintenance, and remote monitoring.
Our Platform should be hardware Agnostic for easy integration with a broad variety of sensors, controllers, machines, and device gateways. Therefore,  enabling many-to-many interoperability between them.Interoperability enables separate parts of the production line  to become more responsive and above all capable to instantly react to different events.

Failure prediction and troubleshooting also become reliable and straight forward.
Moreover, security is critical for Internet of things projects just like any other enterprise solution. Careful identification, encryption, and compression before processing is must. A comprehensive governance model is necessary to restrict access to sensitive data and reports. Policies will define which roles and personas should  control the devices, and accessing the business intelligence dashboards. Internet of things security should be in tight integration with existing corporate policies and security best practices.

Above all, the identification and implementation of the complex business rules that define various policies for connecting to the devices and accessing the data is done.

Factor in machine learning and predictive analytics: Step 4

Insights based on intelligent algorithms realize the real value of IoT.
However, machine learning and predictive analytics is required for every implementation. The chances are that it may become a critical requirement in the future.
Architects should leave enough room for extensibility while defining the data pipeline for processing the sensor data.
In conclusion, it will become easy to add predictive analytics to an IoT solution at a later point.

Near Real-time Analytics: Week 5

The monitoring and analysis of generated individual data point  is necessary . For instance, 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. Therefore, triggering an immediate action within milliseconds of the detection of  the anomaly. The other scenario that demands near real-time processing is healthcare. Monitoring of vital statistics of the patients.
As data enters the IoT platform, an ingestion layer 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. Above all, 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