5 ways the IoT must improve : Deloitte

#News(General) [ via IoTForIndiaGroup ]

If you think you know the problems facing the Internet of Things (IoT), a new Deloitte report, Five vectors of progress in the Internet of Things, offers a great chance to check your assumptions against the IoT experts.
5 IoT challenges
Let’s take a look at all five “vectors of progress,” recast as the challenges they really are, and then get some insight from Schatsky, a Deloitte managing director and resident “trend sensor,” on IoT’s biggest opportunities.

1. Security holes
2. Platform problems

Lack of standards and platforms has made developing and deploying complete IoT solutions more difficult than it should have been, but many vendors are now introducing IoT platforms designed to make it easier to integrate IoT hardware, networks, and applications. Building multivendor solutions has long been the hardest part of crafting complete IoT implementations, but new vendor partnerships are now leading to integrated ecosystems that include dozens of major vendors offering pre-integrated third-party technologies. Another way vendors are tackling the integration issue is with “vertical” integrations that combine sensors, devices, analytics, and other components to create turnkey IoT solutions.

3. Expensive, power-hungry networks

IoT devices need networks to communicate with each other, but traditional WANs are relatively expensive and power-hungry. In response, hundreds of low-cost, low-power wide-area networks (LPWANs) are providing far cheaper connectivity and allowing even small battery-powered devices to last for years.

4. Hard-to-analyze data
5. Latency

Analyzing IoT data in the cloud can introduce latency, making it difficult to generate useful real-time alerts and degrading performance in industrial, enterprise, and smart city settings. In response, the report says, “Analysis of data generated from IoT devices is increasingly occurring not in the cloud but at the network ‘edge,’ physically close to where the data is generated — on local servers, micro data centers, or even on the device generating the data.” Analyzing data at the edge can also help trim data transmission and storage costs.

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