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Most of us can remember life before “smart” devices; smart speakers, smart thermostats, smart homes and the like. It wasn’t that long ago that our devices were like a bunch of loners at a party – they didn't talk to each other.
Your thermostat didn't know your temperature preferences depending on the time of day and your watch couldn’t tell you how many miles you ran.
Which makes the fact that most of us also now rely on several IoT devices throughout our lives daily, pretty fascinating and, in the history of technology, a pretty rapid mass adoption.
The Internet of Things (IoT) has transformed the way we interact with technology and the world around us. It has completely changed how we interact with everyday objects and appliances and revolutionized industries, from healthcare to manufacturing.
So, how did we get to this point of interconnected magic? Get ready for a wild ride!
The concept of connecting devices and machines to the internet predates the term "IoT." In the mid 20th century, researchers and innovators began exploring ways to link physical objects to the digital world through radio-frequency identification (RFID).
One early and notable example of RFID technology being used for IoT-like purposes was during World War II.
In the 1940s, the British Royal Air Force used an early form of RFID technology to distinguish between friendly and enemy aircraft. They developed a system known as "Identification Friend or Foe" (IFF), which used radio waves and transponders to help radar operators identify aircraft.
Decades later, in the early 1990s, is when we first hear the term "Internet of Things," coined by British technology pioneer Kevin Ashton, who envisioned a world where everyday objects could communicate with each other and with us.
In all reality, IoT as we know it really only kicked off 20 years ago in the early 2000s marking a significant turning point in IoT software development.
Key developments during this era included embedded systems and wireless connectivity.
IoT software often ran on embedded systems with limited resources. Developers had to optimize code for these constraints while ensuring reliability and security.
In the early 2000s, one of the prime examples of IoT software running on embedded systems with limited resources was the development of smart thermostats. Developers had to optimize code for these constraints while ensuring reliability and security.
A notable product in this category was the first-generation Nest Learning Thermostat, which was introduced in 2011.
The Nest thermostat is essentially a small, specialized computer designed to control the heating and cooling systems in a home. It featured a microcontroller and limited memory and processing power, which are common characteristics of embedded systems.
The Nest Learning Thermostat, along with other early smart thermostats, played a pivotal role in the popularization of IoT in homes.
These devices not only optimized energy usage but also showcased the challenges and opportunities associated with running IoT software on embedded systems with limited resources. They paved the way for the development of a wide range of IoT devices that we see today, from smart lights to connected appliances and wearable technology.
The rise of wireless communication technologies, such as Wi-Fi and Bluetooth, made it easier to connect devices to the internet, increasing the feasibility of IoT applications.
In the early 2000s, one of the notable IoT devices that heavily relied on wireless connectivity was the OnStar system, particularly the OnStar telematics service offered by General Motors (GM).
OnStar, which was introduced in the late 1990s and continued to evolve in the early 2000s, provided a range of automotive-related services through wireless communication including remote vehicle diagnostics, stolen vehicle tracking, automatic crash response, and emergency service requests.
The OnStar system in the early 2000s exemplified the use of wireless connectivity in IoT devices, particularly in the automotive sector. It demonstrated the potential of connected vehicles for improving safety, security, and convenience through the use of wireless networks and remote communication with service centers.
As we entered the mid-2010s, IoT software development gained momentum and what we think of now as well-known brands relied heavily on these technology advancements.
The integration of IoT with cloud computing platforms allowed for scalable, real-time data processing and storage. This shift reduced the computational burden on IoT devices.
Amazon Web Services (AWS) IoT played a significant role in leveraging cloud computing technologies during the 2010s to advance the Internet of Things (IoT) ecosystem.
Their use of cloud computing empowered organizations to build, scale, and secure IoT solutions efficiently. It streamlined device management, data processing, and analytics, and enabled the development of innovative IoT applications across various domains.
Standardization efforts led to the development of IoT-specific communication protocols like MQTT and CoAP, enhancing interoperability between devices and applications.
One prime example of an IoT product in the 2010s that heavily relied on standard protocols is the Philips Hue smart lighting system.
By relying on established and widely accepted communication standards, Philips Hue was able to offer interoperability with a range of other smart home devices, voice assistants, and IoT platforms.
This not only made it more user-friendly but also encouraged the development of a vibrant ecosystem of third-party applications and integrations, enhancing its capabilities and utility in the IoT landscape of the 2010s.
As IoT products were really taking off around this time, increased awareness of IoT security vulnerabilities prompted developers to prioritize security measures, such as encryption and authentication, to protect data and devices.
One prominent example of an IoT product that placed a strong emphasis on security in the 2010s was the August Smart Lock.
The August Smart Lock is a connected smart lock designed to enhance the security of residential homes while providing convenient remote access.
The August Smart Lock used secure authentication, data encryption, access control, a secure mobile app, physical security features (being a lock and all), security auditing , firmware updates and secure remote access.
The August Smart Lock served as a model for how IoT products in the 2010s could prioritize security to gain the trust of consumers and improve overall safety and convenience.
IoT generated vast amounts of data and developers quickly started seeing the opportunity of leveraging big data analytics and machine learning to derive actionable insights from this data, paving the way for predictive maintenance and improved decision-making.
One notable example of an IoT product that heavily relied on data analytics in the 2010s is the Fitbit wearable fitness tracker and associated platform. Fitbit's devices and ecosystem were built on the extensive collection and analysis of health and fitness data.
Fitbit's success in the 2010s was built on its ability to collect, analyze, and visualize health and fitness data, empowering users to make informed decisions about their well-being and helping healthcare professionals and researchers gain insights into health trends and outcomes. It was a prime example of how IoT devices could harness data analytics to drive personal health and wellness.
The present landscape of IoT software development is marked by advanced technologies and a diverse range of applications.
Tech foundations like 5G Connectivity and Edge Computing, will drive the next wave of IoT software development.
5G Connectivity, which provides ultra-fast, low-latency connectivity, enabling real-time applications like autonomous vehicles and augmented reality in IoT. One modern IoT company that relies heavily on 5G connectivity is "Skydio," a manufacturer of autonomous drones, particularly the Skydio 2 and Skydio X2 drones.
These drones are designed for various applications, including professional cinematography, inspection of critical infrastructure, search and rescue missions, and more. They heavily depend on 5G connectivity for real-time data transfer, remote monitoring, and control.
Edge computing is processing data closer to the source and reducing latency and bandwidth usage.
One modern IoT company that relies heavily on edge computing is "Tesla, Inc." The electric vehicle (EV) manufacturer utilizes edge computing in its vehicles to support various advanced features and autonomous driving capabilities.
Tesla's reliance on edge computing is a key factor in delivering its advanced driver-assistance and autonomous driving capabilities. This approach enhances both the safety and responsiveness of their vehicles while providing a robust platform for ongoing development and improvement of their software and autonomous driving features.
In the years to come, the evolution of IoT software development will be marked by several transformative technologies.
AI and Machine Learning will empower IoT devices to operate with increased intelligence, enabling autonomous decision-making and adaptability to varying environmental conditions.
The integration of blockchain technology will bolster security and transparency in IoT transactions, particularly within sectors like supply chain and healthcare, ensuring data integrity and trustworthiness.
Simultaneously, the intensification of efforts to establish interoperability standards will foster seamless communication and integration across diverse IoT ecosystems, streamlining device collaboration.
Lastly, IoT's expanding role in sustainability, with applications in energy management, waste reduction, and environmental monitoring, will drive environmentally responsible practices and make sustainability a core aspect of IoT software development.
The history of IoT software development reflects an incredible journey from early concepts to a transformative force in our lives today in a very quick amount of time.
As we move forward, IoT promises to bring even more innovation, connecting devices, people, and data in ways we are just beginning to imagine. If you look at the history of technology, it is still so young and we have yet to learn all the possibilities that lie ahead.
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