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IoT-Enabled Services for Sustainable Municipal Solid Waste Management in India
Published in Biswaranjan Acharya, Satarupa Dey, Mohammed Zidan, IoT-Based Smart Waste Management for Environmental Sustainability, 2022
Hrishikesh Chandra Gautam, Vinay Yadav, Vipin Singh
Indore city in Madhya Pradesh has a waste generation capacity of 1,100 tons per day. The city's municipal corporation was facing the issues of not knowing whether all the waste had been collected, assessment of the quantity of wet and dry waste collected, as well as data manipulation in the amount of waste collected and trips taken. An integrated IoT-based system was developed for the city to address these issues in a timely and efficient manner. The door-to-door collection vehicles were equipped with GPS and RFID tags. The vehicles are automatically read with the help of an RFID tag at the respective transfer station, and entry of unauthorized vehicles is stopped. Real-time data is recorded, transferred, and analyzed at the command center. When the waste collection vehicle equipped with GPS and RFID reaches the weighbridge, the automated barrier can read the RFID tag and open. The vehicle weighing operation is conducted in three stages. At the first weighbridge the vehicle is weighed. Then the vehicle unloads the dry waste, and weight is recorded at the second weighbridge. Wet waste is unloaded, and the vehicle is weighed at the third weighbridge. The compiled data is communicated to the central command center in real time. The data of distance travelled between collection sites and the processing facility, and the amount of dry and wet waste collected by each vehicle is recorded and analyzed for all departments at the command center. The system has optimized the day-to-day operation costs, time spent, and manpower utilized. The system has stopped the manipulation and tampering of collected data by removing human intervention in the data collection process. The accurate data is used for future planning and development as well as further optimization of the waste collection process.
Experimental study on soft rock subgrade reinforced with geocell
Published in Road Materials and Pavement Design, 2021
Xingwen Luo, Zheng Lu, Hailin Yao, Jingbo Zhang, Wei Song
After the reinforcement treatment of the soft rock subgrade is completed, a field driving test is conducted. The test vehicle is loaded in one of three ways, with no load, half load or full load. The total weight of the test vehicle with no load is the self-weight of the vehicle. Before the test, the self-weight of the test vehicle is 17.7 tons, measured by the weighbridge. This weight can be decomposed as follows: the front axle load is 6.3 tons, the rear axle load (double-axle) is 11.4 tons. The total weight of the test vehicle at half load is the sum of the self-weight of the test vehicle and a load of 14.1 tons; the total weight of the test vehicle at half load is 31.8 tons, with 7.6 tons on the front axle and 24.2 tons on the rear axle (double-axle). The total weight of the test vehicle at full load is the sum of the self-weight of the test vehicle and a load of 25.9 tons; the total weight of the test vehicle at full load is 43.6 tons, with 9.0 tons on the front axle and 34.6 tons on the rear axle (double-axle). The field driving tests with different load are shown in Figure 6. The dynamic soil pressure test results of the soft rock subgrade in the field driving test are shown in Tables 3–5. The dynamic soil pressure attenuation ratio of the four treatment plans under different vehicle load are shown in Figure 7.
Multi-performance analyses and design optimisation of hydro-pneumatic suspension system for an articulated frame-steered vehicle
Published in Vehicle System Dynamics, 2019
Yuming Yin, Subhash Rakheja, Paul-Emile Boileau
The vehicle model incorporates three-dimensional kinematics of the AFS subsystem during steering, and the dynamic forces developed by the steering struts applied to the strut mounting locations (Figure 1). The strut forces yield an articulation moment about the articulation joint and steering of the articulated vehicle units. Identical driving torque is initially considered to be developed by each wheel, which is subsequently adjusted based on the difference between the actual and target speeds. For this purpose, a proportion-integral (PI) control scheme is used to ensure nearly constant forward speed during a given manoeuvre. The dimensional and inertial parameters of the vehicle, obtained from the computer-aided design (CAD) documents and the weighbridge measurements, are listed in Table 1. The moments of inertia of the two units and the payload are computed with respect to the centre of gravity (cg) of each component. The table also lists the inertial and geometric properties of the articulation, and inertial properties of the steering struts, while the kinematic characteristics of the steering struts have been presented in detail in [4].