IoT Sensor Deployment Challenges & How To Resolve Those – Part 2

This blog series drives awareness about the challenges enterprises commonly face while installing and managing IoT sensor deployments… and the solutions to overcome those challenges.

The first blog of this series discussed the challenges enterprises commonly encounter when deploying IoT sensors.These deployment inefficiencies negatively affect both operating expenses and end-user experience.

This further underscores the necessity to build solutions to simplify and streamline IoT sensor deployment. Some of the key expectations from such an IoT solution would be:

1. Work with a variety of sensor technologies:
To support the wide variety of use-case scenarios, the IoT connectivity landscape is replete with a number of wireless protocols such as LTE-M, NB-IoT, Sigfox, LoRa. In smart building applications, Wi-Fi is common while 4G/LTE and the emerging 5G-IoT standards have a strong presence in industrial and smart-city use-cases. Sometimes even a single IoT use case may involve more than one connectivity technology. This emphasizes the need to engineer a solution that can work seamlessly with the various chipsets corresponding to the sensor technologies.

2. Intelligence to assess network health
To select where the sensor should be installed, you need insight into the network health. Reliable signal strength is important to avoid malfunction due to poor connectivity. The ability to measure the signal quality at a particular spot with a high degree of confidence before installing the sensor significantly reduces the chances that you’d need to remediate connectivity issues post-deployment. That means a reduction in truck rolls and associated deployment cost which also translates to lower TCO and more reliable run time performance.

3. Network visibility post-deployment
When you have visibility into the network health data, you can validate your network and RF design assumptions based on statistical models. The empirical data that you obtain while measuring the network metrics can be analyzed to compare different markets and their respective performance KPIs,which enables monitoring of current operations and plan for the future.

4. Improve IoT deployment efficiency
The inefficiencies and associated cost to remediate problems due to poor connectivity could be substantial. For example, when a thousand connected parking meters are deployed in a city block, and 20% of the locations have poor connectivity, the number of truck rolls and cost-to-repair is significant. The technology to accurately measure signal strength pre and post-deployment is key to enhance deployment efficiencies as it enables you to install IoT sensors with a high-level of connectivity guarantee.

5. Economical and User-friendly
Most IoT use cases involve low-cost sensors to measure water pressure, electricity, vibration, etc. It is important to resolve the problems of IoT sensor deployment with solutions whose economy fits in that price bracket.
Moreover, network evaluation could get quite complicated as it involves many protocols and parameters. The sensor deployment technicians are not necessarily proficient with those technologies. So it is more practical to design a solution that can abstract the technical complexities into simple, user-friendly readings and color cues.

Learn more about Nivid technologies IoT sensor deployment solution that has been engineered to specifically meet these expectations.