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IoT Network Management: 3 Strategies for Device Integration in '24

Updated on May 23
5 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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The Internet of Things (IoT) is transforming businesses by enabling smart device integration and creating interconnected systems that enhance efficiency, productivity, and innovation. Effective IoT network management is crucial for seamless device integration, ensuring optimal performance, and maintaining robust security.

In this guide, we explore effective IoT network management solutions and strategies, from ensuring secure device connectivity to scaling your network safely.

1. Centralized Management

Centralized management platforms consolidate the monitoring and controlling of everything. Focusing on device management in a single system of record allows an enterprise to harmonize its operations and untangle the clutter associated with the management of a million devices. This will include:

Better operational visibility: real-time insights into the status and performance of all connected devices make sure data is available and helps in effective proactive maintenance and troubleshooting. Streamlined Updates: You will be able to deploy firmware and software changes across all your devices, avoiding the manual, time-consuming activities of searching for consistency and lowering the downtime that might be.

Implementing Centralized Management

  • Select an End-to-End IoT Platform: Choose a platform that supports a broad range of different device types and is equipped with management capabilities that include remote monitoring, automated updates, and data analytics.
  • Standardize Device Protocols: IoT devices should be standardized to common communication protocols in order to ensure that they are implemented and compatible with the center system.
  • Invest in Training: Provide IT teams with the skillset to manage and use the centralized platform effectively.

2. Edge Computing

Computing is a computation process near its source, close to the edge of the network, not inside a centralized data center. This presents the following benefits when applied to the integration of IoT devices:

Reduced Latency: Edge computing decreases the time required for data transmission by processing data literally at the very edge, hence improving response time and better real-time decision-making.

Reduced Bandwidth Usage: Offloading data processing to the edge ensures less data is passed to the central servers, which reduces bandwidth and its attendant costs.

Increased Reliability: Edge computing becomes resilient to network failures since local devices can handle the most critical operations without dependency on cloud connections.

Make It Human Edge Computing

To bring edge computing into IoT device integration, businesses should:

  • Deploy Edge Devices: Place edge devices at strategic points where they are able to process and analyze data on the spot. These should be able to support the computational power and storage required to make analyses that can meet the special demands of an IoT network.
  • Build Localized Applications: Develop edge-optimized applications that will run independently in edge environments, meaning they need fewer central servers.
  • Establish data hierarchies: Establish what data should be processed at the edge and what is to be sent to the central servers for further analysis, therefore balancing the workload between local and centralized processing.

Solid Security Protocols

There are vulnerabilities growing in IoT networks as the number of connected devices increases, which leads to cyber threats. Therefore, it is important to put in place stringent security protocols to protect sensitive data and maintain the integrity of the network. These entail important security measures:

Encryption: Protect the data that is at rest and the data in transit such that confidential data cannot be accessed by unauthorized persons. Authentication: Implement strong authentication mechanisms for identification and the device being used by the user for network access. Regular Audits: Ensure that security audits are undertaken on a regular basis to maintain the preparedness of vulnerabilities and to ensure that systems are in compliance with industry standards and regulations.

Making security protocols live To design a secure IoT network, company should:

  • Adopt a security-first approach: consider security in the design and implementation of IoT devices and networks by adopting best practice from the outset.
  • Employ advanced security tools: Such as intrusion detection systems (IDS) and firewalls, to monitor and protect the network against possible threats.
  • Educate stakeholders: Provide continuous training and resources for employees and stakeholders to sensitize them on best security practices and enable them to have the capacity to identify and respond to potential threats.

Performance Monitoring for IoT Systems

IoT network performance monitoring tools:

  • Collect data from devices, gateways, and applications
  • Perform functions such as performance and equipment monitoring
  • Offer features like prompt alerting, visualization, seamless device onboarding, and AI-powered insights

1- Real-Time Network Performance Insights

The significance of real-time monitoring is undeniable. Real-time monitoring of IoT networks plays a crucial role in:

  • Tracking continuous snapshots of network performance
  • Ensuring issues are identified and resolved promptly to prevent operational disruptions
  • Real-time alerting and performance monitoring markedly decrease incident response times
  • Leading to faster issue mitigation and minimizing potential losses.

Monitoring tools, including network monitoring tools, provide valuable insights into data transfer rates, enabling timely adjustments on bandwidth usage and network latency, which directly improves the performance of IoT applications. Transparent visibility of network usage through real-time monitoring tools facilitates cost savings and supports infrastructure optimization by eliminating unnecessary technology expenditures.

Real-time network monitoring underpins predictive maintenance, enabling immediate responses to network incidents and proactively preventing minor issues from escalating into significant equipment failures.

2- Energy Efficiency and Resource Optimization

Given the current era of climate change, energy efficiency has become more significant than ever. Energy efficiency is a main requirement for IoT low power networks to maximize their network lifetime and prevent loss of connectivity. Lightweight cryptography is emerging as an energy-efficient solution suitable for small IoT products like RFID tags and sensor networks.

3- Equipment Monitoring and Predictive Maintenance

Predictive maintenance serves as the foresight tool in the IoT sphere. IoT predictive maintenance applies IoT technology to collect and analyze data for predicting potential equipment failure or outages in a proactive manner. Predictive maintenance leverages machine learning and algorithms to evaluate asset conditions and inform maintenance schedules.

Historical data and pattern analysis through AI enable prediction of device failures and identification of security vulnerabilities. Adopting IoT remote monitoring for predictive maintenance can result in significant cost reductions, lesser equipment failures, and improved customer satisfaction. Continuous performance monitoring and predictive maintenance via IoT enhance productivity and asset performance over their life cycles, while reducing unplanned downtime.

What are the essentials of IoT network management?

Venturing into the IoT domain, we encounter a multitude of choices. The selection of IoT devices and sensors that are reliable, compatible, and adhere to industry standards is fundamental to building a scalable IoT network architecture. But this selection is just the beginning. Smooth operation of these devices necessitates an IoT platform capable of managing device connectivity, multiple communication protocols, and integration with existing business processes. Utilizing device management platforms is essential for seamless functioning and maintenance of the IoT network.

How to scale IoT networks effectively?

As we delve further into the IoT domain, the importance of scalability emerges. A scalable IoT low power network enables the seamless integration of new devices or services while maintaining optimal network performance. This allows for continued expansion without hindering network efficiency. It’s akin to adding more members to a team without affecting the team’s productivity. Recent technological advances such as the development of low power devices are fundamental to the scalability of IoT applications.

If you have questions or need help in finding vendors, feel free to reach out:

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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AIMultiple.com Traffic Analytics, Ranking & Audience, Similarweb.
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Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
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Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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