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Home > NB-IoT > How the IoT Makes Heavy Equipment Safer, More Efficient

How the IoT Makes Heavy Equipment Safer, More Efficient

Update Time: 2022-07-29 17:15:05

How the IoT Makes Heavy Equipment Safer, More Efficient

Heavy equipment represents many vehicles, construction equipment, and bulky industrial machinery. The expectations for heavy equipment are oversized, long life expectancy, and improved equipment performance, as these machines are an essential part of the workflow in many industries. Safety and efficiency are significant concerns for companies that use this type of equipment extensively.

Heavy equipment is mainly used in various industries such as construction, oil and gas, mining, forestry, energy, civil engineering, military engineering, and transportation. Industrial heavy machinery includes construction equipment, wheel loaders, oilfield pieces, bulldozers, hydraulic cranes, dozers, oversized trucks, forklifts, etc. Organizations rely on heavy machinery to speed up production and avoid human error or health risks.

With the development of the Internet of Things, equipment downtime can be reduced while output efficiency is increased. Companies supplying industrial machinery and components are keen on integrating machinery and components connected through the IoT. IoT-driven asset management solutions offer many benefits, including predictive maintenance to prevent equipment failure, increase asset reliability, improve asset health, avoid workplace accidents, and reduce downtime.

IoT Smart Asset Monitoring

Personnel and asset security, theft or burglary of assets, accidents and resulting injuries, and supply chain bottlenecks are common challenges in asset-intensive industries such as manufacturing, utilities, and construction. Many of these challenges can be overcome by improving visibility into daily operations, replacing legacy systems with integrated solutions, and automating manual processes.

Digitization combining connected devices with IoT solutions can help overcome these issues. End-to-end clarity of device status helps improve decision-making, asset reliability, and people and process efficiency. As technology advances, mature organizations have heavy machinery that is computerized, automated, and supports connectivity and big data analytics, which improves efficiency throughout the product development process.

Smart Heavy Equipment in Warehouse Management

Material handling equipment such as trucks, forklifts, pallet trucks, and pump trucks are essential for any warehouse to perform daily activities such as loading, unloading, transporting goods to different areas, and picking from hazardous areas. These machines and their operators need to be properly managed to minimize the chances of accidents. Warehouse operators must take precautions against vehicle accidents and injuries during transportation and take appropriate measures when handling hazardous materials.

Today, future warehouses are using driverless robotic equipment to assist in picking and moving operations. Such warehouses and equipment use guidance systems such as global positioning systems (GPS), lasers, and radio frequency identification (RFID).

For example, advanced driverless pallet trucks and forklifts are equipped with audible warnings and lights and have built-in sensors to detect obstacles. These sensors are equipped with laser or camera systems to detect objects and activity on the floor and determine the height and distance around the vehicle and the corners of the warehouse. This makes the device smart - it knows when to slow down and stop to avoid collisions.

With the latest advances in the Internet of Things for warehouse equipment, new smart forklifts equipped with 360-degree detection forklift antennas have emerged on the market, capable of detecting when workers enter the forklift area. When a worker is detected in a predefined danger zone, audio and visual alerts are sent from inside the forklift cab to alert the operator. This helps reduce the risk of injury and property damage.

Smart Heavy Equipment in Construction

According to a report by MarketandMarkets, the heavy construction equipment market size is expected to grow from $121.46 billion in 2015 to $180.66 billion by 2020, at a CAGR of 7.0%. Based on construction applications, heavy machinery is segmented into four main types.

Earthmoving equipment
Construction vehicles
Material handling equipment
Construction equipment

Wireless technology is having a huge impact on the construction industry that provides connectivity for heavy equipment. These machines use technology-enabled devices combined with cloud computing solutions that allow for the storage and sharing of data.

IoT is key in increasing productivity, improving preventive maintenance, minimizing downtime, and reducing repair costs. Sensors integrated with equipment can detect and send automated alerts related to the status of equipment systems and components. They can also compile and analyze usage and maintenance data to help with preventive and predictive maintenance.

One of the major problems in the construction industry is the injuries caused by accidents involving people and heavy equipment. As the number of heavy equipment increases, so does the risk. The IoT can help make equipment smarter and safer.

In addition, IoT can help track the movement of assets on site or across locations, ensuring that assets are never stolen or lost - a persistent problem on large construction sites that can cause delays and reduce productivity.

Smart Heavy Equipment in Transportation and Logistics

Transportation and logistics companies want to optimize their supply chains. Many transportation companies are already using mobile devices such as bar code scanners, mobile computing devices, and radio frequency identification (RFID) to address supply chain-related challenges. With RFID, many companies achieve high shipping and receiving accuracy, inventory accuracy, and faster order processing while reducing labor costs.

However, company owners have had to pay high costs for accident-related injuries, lost materials, or shipping delays due to driver carelessness while driving heavy trucks or conveyor belts. The risk of these problems can be minimized by using advanced technologies that monitor driver behavior and alert them when a collision is likely to occur.

Computer vision-based technologies and ADAS solutions, along with many in-vehicle sensors, can help with lane detection, traffic signal detection, driver behavior detection, GPS tracking, fuel management, report generation, notification alerts, and predictive maintenance.

Using such solutions, drivers can receive support for accident detection and avoidance. Drivers driving heavy machines can also be monitored, and automatic alerts can be generated if the driver is drowsy or inactive for long periods.

Another effective solution for tracking heavy machines/vehicles are installing GPS fleet tracking devices on the vehicles to get real-time data updates. This is an efficient and secure solution that helps solve problems related to operational inefficiencies, theft, and fleet maintenance, thus increasing the overall productivity of machines and vehicles.


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