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IoT and Edge Computing

Learn more about SPARRO’s industry leading solutions for IoT and Edge Computing.

There’s been a lot of buzz surrounding IoT, or the Internet of Things, in hospitality and residential properties. Beyond simply discussing smart solutions, technology experts often discuss the notion of edge computing. But what exactly does that mean? Edge computing refers to processing data at or near the location where data is collected or used, rather than sending the data to a central location as in cloud computing. Edge computing allows IoT data (in other words, data from smart devices) to be gathered and processed locally, rather than sending the data back to a data center or other cloud-based resource.

Both cloud computing and edge computing involve distributed computing resources (i.e., multiple machines rather than a single device) to perform tasks and execute code. However, edge computing brings the processing and execution closer to where the data is being collected and where the instructions are being executed. According to a recent report by analysts at Gartner, over half of data generated by enterprises is now being processed via edge computing.

Pros and Cons of Edge Computing

Why is edge computing such a popular choice? Some advantages of this approach include:

  • Reduced latency – Data doesn’t need to travel as far, so resulting actions are quicker.
  • Reduced bandwidth and storage requirements – Smaller amounts of data are transmitted locally, rather than sending all data to a central location.
  • Improved security and privacy – Because data is not centralized, a single point of attack won’t render all data vulnerable.
  • Scalability & versatility – Edge computing makes it easier to add processing power where and when it’s needed.
  • Increased operational efficiency – Since data isn’t being sent back and forth between devices and a central cloud, data-based actions can be taken more quickly.
  • Greater continuity – Systems can potentially continue to operate even when the outside network connection is lost. You may temporarily lose the ability to manage systems remotely if that happens, but local data can still be collected and processed and instructions can still be carried out so operations can keep running.

There are potentially some downsides to using edge computing for IoT. For example, it may require more storage at the edge and eventually more bandwidth as usage increases. Also, there is a need to increase security at the edge to avoid local breaches, and solutions must be programmed carefully to avoid discarding useful data (e.g., when processing) that would otherwise be captured centrally. Nonetheless, for many enterprises, the benefits will outweigh the drawbacks.

A key thing to remember is that data processing at the edge can result in faster analytics and quicker responses, which are necessary for the use of smart and AI-based solutions. For real-time automation such as that offered by IoT and smart solutions, edge computing has major advantages over cloud computing, particularly because of lower latency – you can’t implement automation efficiently if you have to wait for data to go to a central location, be processed there, and send instructions back before any action can be taken. Cloud computing may offer greater power for deeper analysis of larger datasets, but if what you’re looking for is an immediate and automated response to conditions, as is necessary for smart solutions, edge computing is the way to go.

What Can Enterprises Do with Edge Computing and IoT?

Edge computing for IoT devices can provide necessary data and controls for intelligent automation, yielding benefits such as energy conservation and cost savings. Faster, more reliable communications enable smart solutions to operate with greater availability, which not only improves efficiency and saves money, but also yields better user experiences. Applications include:

These applications can demonstrate benefits across industries, and there are also a wide variety of applications within specific verticals, some of which are described below.

Residential and Hospitality

In addition to the applications noted above, there are many other potential applications of edge-based smart solutions in smart residences and hospitality properties, including:

  • Implement automated PMS functions such as check-ins, room settings connected to guest preferences, and personalized greetings on in-room devices
  • Enable contactless/self-service options
  • Streamline POS and other back-of-house functions
  • Offer voice controls and BYOD controls
  • Gather better data about guest/resident patterns that can be used to improve operational efficiency and guest-resident experiences

Pre-pandemic studies conducted by PwC indicate that, by 2019, around 70% of hotel managers surveyed said they had already implemented IoT solutions and/or pilots, and more recent data regarding equipment and solution purchases suggests that those numbers are still increasing.

Healthcare

Similarly, in healthcare settings, IoT and IoMT (Internet of Medical Things) solutions have the potential to offer greater insights and better care with lower costs. Healthcare systems are gathering more data than ever, and while some of that data will need more in-depth data processing in a data center or in the cloud, edge processing is crucial for situations that require fast analysis of and responses to data, such as emergency situations, and will also help control the costs of data collection and processing. Some healthcare applications of edge-based IoMT solutions include:

  • Driven by an increase in telemedicine, collect real-time health data from remote devices to enable ongoing monitoring and reporting of potential problems
  • Gain faster diagnosis of and response to events such as heart attacks and strokes
  • Continuously monitor patients in elder care settings, or even at home for patients with chronic illnesses or patients receiving home care, improving access and outcomes while lowering costs
  • Implement smart diagnostic devices in healthcare facilities, including non-hospital facilities such as outpatient centers and urgent care facilities, bringing healthcare decisions closer to the patient
  • Gather better data for planning and keeping track of both staff and equipment
  • Perform faster patient check-ins and improved flow, resulting in lower wait times and increased satisfaction
  • Improve recordkeeping, with more patient data collected and used locally
  • Implement innovative solutions such as connected ambulances
  • Employ more fine-grained tools for maintaining HIPAA compliance, since data is not necessarily centralized

Data indicates that IoT revenue in the healthcare sector reached $74.31 billion in 2022, with an estimated total of $135.87 billion by 2025 (even several times that amount worldwide, depending on whom you ask), and as many as 4 out of 5 healthcare providers are already using IoT devices and solutions.

Energy and Mining

In the energy and mining industries, smart solutions and edge computing can save costs, reduce downtime, comply with regulations, and improve safety with innovative approaches such as:

  • Detect worker fatigue and inattention using body-worn sensors
  • Monitor changes in temperature, humidity, oxygen levels, and pollution levels, along with things like pressure and flow; with more frequent readings and local processing, action can be taken immediately if problems arise (for example, automatically adjusting ventilation systems, or letting workers know when to leave an area and when it’s safe to return)
  • Improve real-time communication between workers and issue critical alerts
  • Perform real-time analysis and response to avoid downtime and disasters
  • Dynamically adjust power supply among distributed networks based on real-time monitoring of production and consumption
  • Automatically adjust power-generating apparatus in response to conditions (for example, automatically adjusting the angle of solar panels to improve alignment for better energy generation)
  • Incorporate AI to learn about things like mineral behavior and equipment failure patterns over time

Although the implementation of IoT networks in energy facilities and especially in mining sites has been uniquely challenging due to issues with connectivity (for example, in locations deep underground, or on sites with much interference from equipment operations), edge-based IoT solutions are increasingly being implemented in these settings with good results in terms of cost and time savings and increased productivity.

Manufacturing

For manufacturing facilities, the sheer amount of data that can be collected across an enterprise essentially requires some use of cloud-based or centralized storage, especially for the analysis of broader patterns; that kind of analysis requires time and bandwidth. However, there are numerous ways to improve operations within facilities using edge-based IoT and IIoT (Industrial IoT) solutions, including:

  • Tie together sensors, actuators, robotics, and more to increase efficiency across processes and functions
  • Reduce latency by using machine-to-machine communications, robotics, and automation to implement actions near the source of the data that drives those actions
  • Analyze data in real time to streamline processes, calibrate equipment, plan production, perform quality control, predict equipment failures, improve safety and security, reduce downtime, and optimize logistics
  • Implement predictive analytics to find opportunities for near-term improvement
  • Tie together functions such as inventory management and production
  • Adjust operations to improve sustainability based on real-time data in specific facilities
  • Overcome challenges with regard to IIoT device interoperability by moving processing to the edge, lessening the need for intercommunication amongst the devices themselves

While cloud computing may be desirable for centralizing and standardizing operations across an entire enterprise, edge computing combined with IoT enables optimization based on the actual conditions in specific locations. This greater flexibility can not only improve safety and functionality where work is being done but can also yield cost savings and improved efficiency. Recent studies indicate that nearly 90% of manufacturers are at least beginning to take advantage of IoT/IIoT edge-based solutions to achieve these benefits.

Transportation and Logistics

In transportation and logistics, there are many potential points of vulnerability, from carrier disruptions to equipment failures, from staff shortages to bottlenecks and more. These points of vulnerability offer many opportunities for improvement using IoT solutions with edge computing, such as:

  • Use real-time data to plan for use of resources and staff, as well as to predict supply shortages or excesses; predict bottlenecks and offer alternative modes of transportation
  • Pinpoint the location and environmental conditions in which cargo is being stored or transported and detect potential problems before they occur
  • Improve automation in warehouses and transportation centers
  • Offer improved driver monitoring and assistance systems and route optimization
  • Implement predictive inventory/asset management
  • Gather weight management data more easily to improve payloads and reduce fines
  • Track factors such as emissions and suggest opportunities for greater sustainability

Again, cloud computing may be necessary to gather and analyze big data for larger, longer-term trends, IoT and edge computing offers opportunities for local and near-term implementation of improvements with faster response times and greater security at a reduced cost.

Retail

Smart solutions, including Consumer IoT (CIoT), combined with edge processing in the retail sector offer benefits both for the retailer and for the customer, such as:

  • Gaining a better understanding of customer habits, such as where they spend the most time in the store and what products are drawing attention, as well as understanding where bottlenecks occur that may hurt the customer experience; real-time data can yield insights for improved store flow, more targeted purchasing, and increased customer loyalty
  • Meeting or exceeding expectations surrounding contactless shopping and self-checkout
  • Managing inventory and product shelving in real time, not only to avoid empty shelves but also to determine what is selling well and what isn’t, what needs increased stock over time and what trends are occurring, and even when to change item positioning based on buying patterns
  • Monitoring environmental data, for example, to avoid food spoilage and losses and to manage energy use; food spoilage in particular is a high-loss area and can be limited with real-time data and alerts
  • Tracking products for loss prevention to avoid theft, vendor fraud, paperwork errors, and other costly incidents
  • Providing up-to-date information desired by customers, including product information, navigation, current specials, and more
  • Implementing innovations such as virtual mirrors and other augmented reality (AR) options
  • Improving security to enable better connections with consumers, for example, by encouraging them to connect their phones for improved shopping experiences, personalized offers, etc.

Especially in light of recent disruptive events such as the COVID-19 pandemic and the increasing preference of under-55 consumers for online shopping, a large majority of retail companies are looking to transform the in-person shopping experience with innovations such as Bluetooth beacons and targeted offers. Edge computing offers the ability to process IoT and CIoT data as events happen, improving retailers’ ability to implement these changes more quickly and increase customer engagement. Without such moment-to-moment data processing, retailers risk missing opportunities that can pass them by before trends and events are even noticed.

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