Tracking extent and impact of deforestation

Heavy industries are usually strategically located close to the raw materials while making the supply chain as effective as possible. Most of the assets are developed in areas with a high level of vegetation. Clearing large tracts of forest cover to pave way for road networks, clear spaces for setting up warehouses and workshop spaces poses a danger, in that the carbon sinks are cleared in large quantities.

Extraction of raw materials through methods such as open-pit mining similarly results in the clearing of a large territory. Such unsustainable practices pitch industrial players in legal battles with environmental conservation advocates and activists. According to FAO, deforestation is the second largest cause of climate change. It is estimated that forest cover, the size of a standard football field is lost to unsustainable deforestation every second.

Describing the industry as one of the least trusted, it is possible to draw parallels with the movie Avatar, which featured a company destructively mining a rare substance on a distant planet. It is a simple fact that mining is essential to human progress and has been for the last century and more. AI and IIoT are proving a crucial role in combating the negative impact of deforestation and ensure future development of heavy industries and their affiliated activities.

There are a number of ways in which AI and IIoT technology can be integrated into forest cover management in order to support the sustainable development of heavy industries. For instance, when an asset is set up in a remote location, forests may be cleared to pave way for development, while at the same time creating a loophole through which illegal deforestation and logging can be performed. In order to avoid this, some development in acoustic sensor technology is taking shape, which is able to detect any illegal felling of trees. A typical system that heavily relies on this approach to support forest conservation measures was developed by RFCx.

Drone technology, coupled with satellite imagery can be used as a tool to study forest covers, before, during and after the establishment of industrial practices within a forested zone. This allows the stakeholders to specifically identify the size of the forests, identify the dominant species and assess the growth patterns of forests. Through this method, they are able to gain an insight on how much cover is lost over a given project, they can then analyse the data collected to systematically decide on expanding or downscaling their operational practices.

Other companies are advancing AI and IIoT technology to incorporate humidity, soil condition and moisture level sensors in forests to gain real-time insight on the forests’ health. Through this data, we are able to analyse and predict events such as forest fires, drought or the general response of forests to changes in the size and intensity of forest covers.

Heavy industries similarly emit gases and particulates to the environment and can be dispersed over a wide area, way beyond the setup of the industrial establishment. These emissions mix with rainwater and atmospheric humidity, falling down as rain and can adversely affect vegetation as a result of acidic rain. The impacts of such an eventuality can result in stunted growth of forest cover and ultimately the death of some tree species. As such, integration of smart emission control mechanisms as well as control devices into industrial processes will avert possible deforestation.

Assessment of industrial energy needs

Heavy industries are culprits when it comes to energy consumption. The need for energy-saving approaches is growing as energy needs are directly linked to the profitability of companies. The capabilities of AI and IIoT in shaping the operations can be categorised based on energy needs, smart grids, handling power fluctuations and advancing energy storage strategies.

Smart grids integrate machine learning to identify energy consumption patterns during the various times of the day and perform autonomous energy audits for industrial plants. By applying a broad range of technologies, industries are now able to collect data in real-time, perform analytics and develop a consumption model. The model is then used to optimise energy use and diversify the supply sources, to meet every specific aspect of operations. An advanced AI and IIoT platforms will allow heavy industry managers to switch between renewable energy sources. During peak hours, when the industry is operating at full capacity, smart grids will maximise usage of power from a renewable energy source, cutting down the need for power from conventional sources such as coal-powered plants or diesel generators.

The growing production calls for the utmost conservation of energy resources. This has led to a big investment in the development of renewable energy technologies, namely wind and solar, which may at times produce excess energy during their peak operating time. The excess energy has to be stored for future use when generation from these sources are at a minimum. AI and IIoT help heavy industries to study generation and usage patterns, perform forecasts on renewable energy availability and perform predictive maintenance on storage and distribution sources themselves.