Internet of Things, a concept in use since the introduction of RFID sensors, has caused fervor in the current times for a lot of reasons. The further in IoT can be attributed to low cost but high end sensors, and the advances made by both wired and wireless technology. Your data processing and analysis techniques and platforms have advanced in such a way that you gain all the necessary insights in an easier way. Communication between humans and technology has advanced with the help of sensors and other closely connected devices. With this advance, businesses can establish newer models to offer their services in a better way using Internet of Things.
While, Internet of Things advances all communication between humans and device interfaces, you will observe some technology challenges that come with this concept applied to business models. Here we will unlock some of the key technology challenges of IoT.
Managing the Devices
When you are working with sensors, gateways and devices, you will sometimes find that they are spread across geographical locations. They can be located in remote or inaccessible locations too! You will need to ensure that these different devices are totally automated, and can be managed from remote locations too.
Diversity and Interoperability of Devices
Let’s say there is a business model that is completely sensor enabled and you need to monitor it real time. You will find that the sensors enabled throughout the model do not restrict themselves to a single vendor. This simply means that the standards for the different products may be different, which in turn cause interoperability issues. You need to identify this challenge, and work towards mitigating it.
Integration of Multiple Devices
When you are working with Internet of Things, you will find your data coming from different sources. Some examples of the sources could be sensors, data from the mobile device, social network feeds etc. The semantics of this data should be part of the data and should not be a part of the application logic stored in the application silos.
Data Volume & Performance
As a business, you will be asked to manage the scale, data volume as well as performance of the different elements of the IoT applications. When the users and devices for the IoT application rise, the data volume to be integrated and analysed will also rise. This might hinder the performance of the application. With big data related issues and standard architecture needs, your platform might seem inadequate. While, you are still involved in all this, you also need to manage real time performance parameters, and consider the application level latencies.
Flexibility and Evolution
The sensors and devices associated with your IoT applications will keep evolving, and there’s no stopping that. You will need new capabilities, which will in turn require new algorithms and new analytical techniques. You will be asked to create new apps with minimal effort and with quick turn- around time. The ecosystems which you thus build will require platforms that can enable and sustain these new apps that you have created.
IoT poses to be a complex ecosystem, and you will be working with multiple stakeholders. You will see that the end-to-end IoT applications require several technologies, activities and entities. You will need to work hard as a collaborative player, and work towards combining the different entities.
Semaphore Software has experience and expertise in developing Internet of Things solutions to give you a better and interconnected ecosystem for real time updates and faster communication. Contact us via email@example.com to discuss your requirement in detail.