What is the Internet of Things (IoT)?

In the simplest terms, the Internet of Things (IoT) represents all computing devices that are connected to the internet. It can be described as a network of responsive devices and everyday objects that wouldn’t necessarily be thought of as communicating with the internet like wearables, industrial machinery, motion sensors, and more. These devices are embedded with environmental sensors and other technologies that enable them to collect and exchange data without human intervention.

Originally, the industrial and automotive sectors were some of the first pioneers in IoT, connecting their machines to talk to one another and report back with potential failures or overloads. Usually in the industrial sector, IoT is named Industrial IoT or in the shorter version IIoT.

What does the edge mean?

If you have heard the term “edge” in reference to the IoT, it is an area that is closer to the end user or physical location than a data center (cloud or on-premises). Edge computing is about moving data processing from those data centers to devices at the network edge

In the early stages, IoT devices simply recorded data and transmitted it. Now, with advances in machine learning, microservices, and extremely lightweight integration frameworks, devices can be programmed to take their own actions or respond to events happening in their environments.

Since we pushed all the processing power to the edge, it’s important for the data to be analyzed and processed in real-time there too. By moving intelligence to the edge, this greatly reduces latency time. If every piece of data had to be uploaded to the cloud, processed and then an action determined and transmitted back to devices, the IoT wouldn’t be very useful for today’s real-time consumers. They need instant action. An example of intelligence being moved to the edge comes from CargoSmart. CargoSmart developers embedded machine learning models into their edge devices so that if conditions change on the ship, IoT temperature sensors can raise events that can be alerted on and visualized for those manufacturers in real-time.

Challenges to IoT adoption

With the plethora of endpoints and technologies available, many organizations struggle with integration, hyper-interoperability, master data, security, analytics, and a common semantic layer across the architecture. IoT presents a new set of skills that may not exist within many Enterprises. To make the IoT successful, organizations need to integrate various disparate applications, data, systems, people, and sensors. Furthermore, once everything is connected, they need a way to analyze and track all the data coming from their devices.

Common challenges include:

  • IoT data present scalability and integration challenges to harness and gain business insights.
  • Communication and endpoint IoT technologies are rapidly evolving, with numerous competing and fragmented standards and protocols.
  • The deployment of IoT technology introduces a multifaceted "attack surface" that must be secured.

Technical opportunities to improve IoT adoption

  • Advances in artificial intelligence algorithms, advanced analytics and new data management approaches enabled by abundant computational power can expedite the delivery of business outcomes.
  • IoT communications networks should be implemented to balance network efficiency and compatibility.
  • IoT's multifaceted attack surface can be secured with new and innovative approaches in IoT security.

Top use cases globally

The Internet of Things presents vast opportunities in almost every industry. From remotely controlling crop irrigation to finding health issues in a person before they present to connected cars, IoT is exploding with opportunities and revenue.

  • Manufacturing Use Cases
  • Food Traceability
  • Maintenance & Field Service
  • Manufacturing Operations
  • Production Asset Management
  • Cross Industries Use Cases
  • Connected Vehicles
  • Smart Buildings
  • Staff Identification
  • Transportation Use Cases
  • Air Traffic Monitoring
  • Fleet Management
  • Freight Monitoring
  • Smart Cities

For example Anadarko, an oil and gas exploration company, uses sensor data on oil rigs to understand the operational health of oil production and drilling. The IoT “Edge” is a series of industrial devices - basically any equipment on the rig that has embedded sensors. Those events are transmitted to a local computing node running streaming analytics, which performs local analytics and automates local action and alerting of conditions on the rig. Then, when the edge is connected (connectivity of many rigs is intermittent), the local edge state is replicated to the IoT Platform, where the aggregation is performed across rigs to achieve a systematics real-time view of all rigs and equipment for higher-level decision making.

Software enabling IoT solutions

Edge-device platform suppliers- These are companies that make or include device components or complete devices for edge devices or gateways. Many edge devices are built around components that license ARM architectures, such as silicon devices from NXP Semiconductors or Qualcomm. Choosing a gateway hardware vendor such as Cisco, Dell, HPE, or Libelium drives customers toward certain software solutions and implementation services providers they’ve partnered with.

Solution stack providers that combine hardware and software- Electric Imp, Particle, and Samsung Artik are offerings with integrated stacks of devices, software, and cloud services. These enable customers to select specific sensors for their use case and implement them as part of near turnkey solutions.

Product lifecycle management (PLM) software with integrated IoT software partners- Traditional PLM software helps firms orchestrate the design, production, and support of products. Vendors such as Dassault Systemes, PTC, and Siemens have acquired or partnered to integrate with IoT software platforms to facilitate the development of connected products by combining the mechanical, electrical, and software BOM and iterate designs interactively among stakeholders.

IoT software platforms, often pre-integrated with edge devices- Arrayent, Exosite, LogMeIn’s Xively, and PTC’s Thingworx —offer tailored solutions that connect, manage, and secure IoT devices in specific scenarios, while also offering sufficient data integration and analytics to deliver business value. Industrial players such as Bosch SI, GE Digital, and Schneider Electric are developing offerings for a broad set of industrial and commercial use cases. Enterprise software players such as AWS, IBM, and Microsoft are creating IoT-specific features and capabilities for their software platforms to support the new needs of IoT use cases. All are working with specific IoT devices, software protocols, and gateway partners that they certify for their platforms. Some also line up preferred system integration partners, just as PTC does with Wipro.

Capabilities needed to implement IoT

  • Cybersecurity
  • Integration
  • Analytics
  • Network and communications
  • Data management
  • device management
  • App development