Crowd logistics — a paradigm in which deliveries are handled by a distributed network of freelance drivers and everyday commuters — is resha...
Đề bài
Crowd logistics — a paradigm in which deliveries are handled by a distributed network of freelance drivers and everyday commuters — is reshaping last – mile transportation. This model leverages sophisticated mobile apps and geolocation tools to assign parcels to nearby participants and enhance delivery speed. It also collects real – time tracking data on commuter availability and vehicle positioning to coordinate the process effectively. Participants, whether students or retirees, can register through a platform that verifies their identities and preferred travel routes. When a delivery task matches someone’s usual journey, the system incorporates it into their route. The platform monitors package locations during transit and detects deviations such as off – route movements or long idle periods, helping resolve incidents before they escalate. From a sustainability standpoint, crowd logistics provides multiple ecological and economic gains. It capitalizes on pre – existing travel plans, thereby limiting the need for additional transport and cutting emissions. This becomes particularly advantageous in gridlocked cities, where vehicle overpopulation exacerbates air quality and logistical inefficiencies. The model’s lean operating structure and shared workload also minimize financial overhead, allowing it to scale without compromising affordability. Behind the scenes, data analytics synthesize vast repositories of trip data to pinpoint logistical choke points, forecast regional demand fluctuations, and refine routing algorithms. While some platforms use blockchain to confirm package handovers and timestamp arrivals, others rely on cloud – based logs to track service quality and maintain accountability. These mechanisms ensure that delivery histories remain accessible, verifiable, and strategically useful. [Adapted from ResearchGate] Question 23: Which of the following is NOT mentioned in paragraph 1 as a function of crowd logistics systems? C. Gathering real – time data on traffic conditions D. Utilizing geolocation for routing efficiency Question 24: The word “monitors”in paragraph 2 is closest in meaning to __________. A. tracks B. navigates C. controls D. determines Question 25: The word “it”in paragraph 2 refers to __________. A. platform B. delivery task C. journey D. system Question 26: The word “compromising”in paragraph 3 is OPPOSITE in meaning to __________. A. negotiating B. preserving C. weakening D. arguing Question 27: Which of the following best paraphrases the underlined sentence in paragraph 3? A. This system significantly reduces environmental and logistical burdens in developing areas struggling with dense vehicle networks. B. The model shows moderate usefulness in urban spaces that face traffic limitations and delivery slowdowns. C. In urban zones plagued by traffic overload, this approach provides both environmental and operational support substantially. D. Crowd logistics seems reasonably suitable in locations where transit congestion affects system performance. Question 28: Which of the following is TRUE according to paragraph 4? A. Certain platforms make use of blockchain to validate critical delivery milestones. B. Access to delivery records appears to be restricted to a specific group of employees. C. Route optimization tools are sometimes avoided to reduce computational costs. D. Stored data from completed trips is often erased to prevent long – term retention. Question 29: Which paragraph refers to using driver availability data to organize delivery assignments? A. Paragraph 1 B. Paragraph 2 C. Paragraph 3 D. Paragraph 4 Question 30: Which paragraph describes a preventive mechanism to handle potential route problems? A. Paragraph 1 B. Paragraph 2 C. Paragraph 3 D. Paragraph 4 |